Sewage treatment plant operation cost optimization method, device, equipment and storage medium

Abstract

The invention provides a sewage treatment plant operation cost optimization method and device, equipment and a storage medium, and is applied to the technical field of sewage treatment. The method comprises the following steps: acquiring basic data of a sewage treatment plant, and determining corresponding operation rule parameters based on the basic data; inputting the basic data and the operation rule parameters into the pipe network model to obtain a target function value of the sewage treatment plant, the target function value being used for indicating the operation cost condition of the sewage treatment plant; under the condition that the target function value does not meet the preset condition, the operation rule parameters are updated, and a new target function value is determined based on the new operation rule parameters until the target function value meets the preset condition; the target operation rule parameter in the pipe network model is obtained, the target operation rule parameter is the corresponding operation rule parameter when the target function value meets the preset condition, the operation cost of the sewage treatment plant corresponding to the target operation rule parameter is optimal, the operation cost is reduced, and the economic benefit is improved.

Description

Technical Field

[0001] The present application belongs to the technical field of sewage treatment, and in particular, relates to a method, device, equipment and storage medium for optimizing the operating costs of a sewage treatment plant. Background Art

[0002] Sewage treatment plants are important facilities for treating urban domestic sewage and industrial wastewater. Their purpose is to remove pollutants from sewage so that it meets discharge standards or reuse requirements. Sewage quality changes over time and seasons, which affects the treatment capacity and operating costs of sewage treatment plants. Therefore, a method for optimizing the operating costs of sewage treatment plants is needed to ensure that sewage treatment plants operate economically and efficiently.

[0003] In the existing technology, the optimization of sewage treatment plant operation costs mainly focuses on the optimization of the operation rules of a single or multiple pumping stations, without fully considering the impact of pumping station operation on the terminal water quality. Although the optimization of internal process energy consumption of sewage treatment plants can reduce the internal operation costs of sewage treatment plants, it does not involve the control of the water quality of the water inlet at the front end of the pipe network.

[0004] However, the optimization process of sewage treatment plant operating costs in the existing technology does not fully consider the impact of water quality on costs, lacks cost control for plant-network coordinated operation, and over-relies on manual experience, resulting in low efficiency and high operating costs. Summary of the invention

[0005] The present application provides a method, device, equipment and storage medium for optimizing the operating costs of a sewage treatment plant, so as to solve the defects of low efficiency and high operating costs in the prior art methods for optimizing the operating costs of sewage treatment plants.

[0006] In a first aspect, the present application provides a method for optimizing the operating costs of a sewage treatment plant, the method comprising:

[0007] Obtaining basic data of the sewage treatment plant, and determining corresponding operating rule parameters based on the basic data;

[0008] Inputting the basic data and the operating rule parameters into a pipe network model to obtain an objective function value of the sewage treatment plant, wherein the objective function value is used to indicate the operating cost of the sewage treatment plant;

[0009] In the case where the objective function value does not meet the preset condition, the operation rule parameter is updated, and a new objective function value is determined based on the new operation rule parameter until the objective function value meets the preset condition, wherein the preset condition is used to indicate that the objective function value converges;

[0010] The target operation rule parameters in the pipe network model are obtained, where the target operation rule parameters are operation rule parameters corresponding to when the objective function value meets preset conditions, and the sewage treatment plant operation cost corresponding to the target operation rule parameters is optimal.

[0011] Optionally, the inputting the basic data and the operating rule parameters into a pipe network model to obtain an objective function value of the sewage treatment plant includes:

[0012] Controlling the pipe network model to simulate the water quality changes of the sewage treatment plant based on the basic data and the operation rule parameters to obtain corresponding inlet water quality parameters;

[0013] According to the inlet water quality parameter, the concentration value of the target indicator is determined, and according to the concentration value of the target indicator, the objective function value of the sewage treatment plant is determined.

[0014] Optionally, the basic data includes: a plurality of pipelines and a plurality of pumping stations, and the determining corresponding operation rule parameters based on the basic data includes:

[0015] Determining regional distribution information of the sewage treatment plant, the regional distribution information comprising: a plurality of drainage areas;

[0016] For any one of the plurality of drainage areas, according to the plurality of pipelines and the plurality of pumping stations, the pipelines in the drainage area are merged to obtain an association relationship between the merged pipelines and the pumping stations;

[0017] Determine corresponding operation rule parameters according to the basic data and the association relationship;

[0018] The controlling of the pipe network model simulates the water quality changes of the sewage treatment plant based on the basic data and the operation rule parameters to obtain corresponding inlet water quality parameters, including:

[0019] Based on the operating rule parameters, updating the model parameters of the pipe network model;

[0020] The updated pipe network model is controlled to simulate the water quality changes of the sewage treatment plant based on the basic data to obtain corresponding inlet water quality parameters.

[0021] Optionally, the updated pipe network model is controlled to simulate the water quality changes of the sewage treatment plant based on the basic data to obtain corresponding inlet water quality parameters, including:

[0022] Controlling the updated pipe network model to simulate the water quality change process of the sewage treatment plant according to the basic data to obtain the prediction data output by the pipe network model;

[0023] Comparing the predicted data with the actual detection data to determine the performance index of the pipe network model;

[0024] When the performance indicator is greater than a preset value, the predicted data is determined to be the hydraulic parameters of the target sewage treatment plant, and the inlet water quality parameters of the target sewage treatment plant are determined based on the hydraulic parameters.

[0025] Optionally, determining the concentration value of the target indicator according to the inlet water quality parameter, and determining the objective function value of the sewage treatment plant according to the concentration value of the target indicator includes:

[0026] According to the inlet water quality parameters, sediment simulation treatment is performed to determine the suspended solids concentration of the sewage in the sewage treatment plant;

[0027] Determining a target indicator concentration value of the sewage treatment plant according to the suspended solids concentration, wherein the target indicator concentration value is used to indicate the content of organic pollutants in the water body of the sewage treatment plant;

[0028] Calculating the operating cost of the sewage treatment plant according to the target indicator concentration value;

[0029] The objective function value of the target sewage treatment plant operating cost is determined according to the operating cost.

[0030] Optionally, the calculating the operating cost of the sewage treatment plant according to the target indicator concentration value includes:

[0031] Determining the unit electricity consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value;

[0032] Determining the unit drug consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value;

[0033] The operating cost of the sewage treatment plant is determined according to the unit electricity consumption cost and the unit drug consumption cost.

[0034] Optionally, the operating rule parameters include: the operating time of the pump station and the start and stop frequency of the pump station, and the objective function value of determining the operating cost of the target sewage treatment plant according to the operating cost includes:

[0035] For any one of the plurality of pumping stations, calculating the dispatching cost of the sewage treatment plant according to the operation time of the pumping station and the start and stop frequency of the pumping station;

[0036] The objective function value of the sewage treatment plant is determined according to the operating cost and the scheduling cost.

[0037] In a second aspect, the present application provides a sewage treatment plant operation cost optimization device, the device comprising:

[0038] Acquisition module, used to obtain basic data of sewage treatment plants;

[0039] A determination module, used to determine corresponding operation rule parameters based on the basic data;

[0040] A processing module, used for inputting the basic data and the operating rule parameters into a pipe network model to obtain an objective function value of the sewage treatment plant, wherein the objective function value is used to indicate the operating cost of the sewage treatment plant;

[0041] The processing module is further configured to update the operation rule parameters if the objective function value does not meet the preset conditions, and determine a new objective function value based on the new operation rule parameters until the objective function value meets the preset conditions, wherein the preset conditions are used to indicate that the objective function value converges;

[0042] The acquisition module is also used to obtain the target operation rule parameters in the pipe network model, the target operation rule parameters are the operation rule parameters corresponding to the objective function value when the preset conditions are met, and the sewage treatment plant operation cost corresponding to the target operation rule parameters is optimal.

[0043] Optionally, the processing module is further used to control the pipe network model to simulate the water quality changes of the sewage treatment plant based on the basic data and the operation rule parameters to obtain corresponding inlet water quality parameters;

[0044] The determination module is also used to determine the concentration value of the target indicator according to the inlet water quality parameter, and determine the objective function value of the sewage treatment plant according to the concentration value of the target indicator.

[0045] Optionally, the determination module is further used to determine the regional distribution information of the sewage treatment plant, and the regional distribution information includes: a plurality of drainage areas;

[0046] The processing module is further used to merge the pipes in any one of the plurality of drainage areas according to the plurality of pipes and the plurality of pumping stations, and obtain an association relationship between the merged pipes and the pumping stations;

[0047] The determination module is further used to determine corresponding operation rule parameters according to the basic data and the association relationship;

[0048] Optionally, the processing module is further used to update the model parameters of the pipe network model based on the operation rule parameters;

[0049] The processing module is also used to control the updated pipe network model to simulate the water quality changes of the sewage treatment plant based on the basic data to obtain corresponding inlet water quality parameters.

[0050] Optionally, the processing module is further used to control the updated pipe network model to simulate the water quality change process of the sewage treatment plant according to the basic data to obtain the prediction data output by the pipe network model;

[0051] The determination module is further used to compare the predicted data with the actual detection data to determine the performance index of the pipe network model;

[0052] The determination module is further used to determine that the predicted data is the hydraulic parameter of the target sewage treatment plant when the performance indicator is greater than a preset value, and determine the inlet water quality parameters of the target sewage treatment plant based on the hydraulic parameters.

[0053] Optionally, the sewage treatment plant operation cost optimization device further includes: a calculation module;

[0054] The determination module is further used to perform sediment simulation processing according to the inlet water quality parameters to determine the suspended solids concentration of the sewage in the sewage treatment plant;

[0055] The determination module is further used to determine a target indicator concentration value of the sewage treatment plant according to the suspended solids concentration, wherein the target indicator concentration value is used to indicate the content of organic pollutants in the water body of the sewage treatment plant;

[0056] The calculation module is used to calculate the operating cost of the sewage treatment plant according to the target indicator concentration value;

[0057] The determination module is further used to determine the objective function value of the operating cost of the target sewage treatment plant according to the operating cost.

[0058] Optionally, the determination module is further used to determine the unit electricity consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value;

[0059] The determination module is further used to determine the unit drug consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value;

[0060] The determination module is further used to determine the operation cost of the sewage treatment plant according to the unit electricity consumption cost and the unit drug consumption cost.

[0061] Optionally, the calculation module is further used to calculate the scheduling cost of the sewage treatment plant for any one of the multiple pumping stations according to the operation time of the pumping station and the start and stop frequency of the pumping station;

[0062] The determination module is further used to determine the objective function value of the sewage treatment plant according to the operating cost and the scheduling cost.

[0063] In a third aspect, the present application provides a sewage treatment plant operation cost optimization device, comprising:

[0064] Memory;

[0065] processor;

[0066] Wherein, the memory stores computer-executable instructions;

[0067] The processor executes the computer-executable instructions stored in the memory to implement the method for optimizing the operating costs of a sewage treatment plant as described in the first aspect and various possible implementations of the first aspect.

[0068] In a fourth aspect, the present application provides a computer storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the method for optimizing operating costs of a sewage treatment plant as described in the first aspect and various possible implementations of the first aspect.

[0069] The present application provides a method, device, equipment and storage medium for optimizing the operating cost of a sewage treatment plant. The method obtains basic data of the sewage treatment plant and determines corresponding operating rule parameters based on the basic data; inputs the basic data and operating rule parameters into a pipe network model to obtain the objective function value of the sewage treatment plant, which is used to indicate the operating cost of the sewage treatment plant; when the objective function value does not meet the preset conditions, the operating rule parameters are updated and a new objective function value is determined based on the new operating rule parameters until the objective function value meets the preset conditions; the target operating rule parameters in the pipe network model are obtained, the target operating rule parameters are the operating rule parameters corresponding to the objective function value when the preset conditions are met, and the sewage treatment plant operating cost corresponding to the target operating rule parameters is optimal, the operating cost is reduced, and the economic benefits are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0071] Figure 1 Schematic diagram of the process of optimizing the operating cost of a sewage treatment plant provided for this application Figure 1 ;

[0072] Figure 2 Schematic diagram of the process of optimizing the operating cost of a sewage treatment plant provided for this application Figure 2 ;

[0073] Figure 3 Schematic diagram of the process of optimizing the operating cost of a sewage treatment plant provided for this application Figure 3 ;

[0074] Figure 4 A schematic diagram of the structure of the sewage treatment plant operation cost optimization device provided for this application;

[0075] Figure 5 Schematic diagram of the structure of the sewage treatment plant operating cost optimization equipment provided for this application.

[0076] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0077] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in this application will be clearly and completely described below in conjunction with the drawings in this application. Obviously, the described embodiments are part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0078] The terms "first", "second", "third", "fourth", etc. (if any) in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in sequences other than those illustrated or described herein.

[0079] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0080] Sewage treatment plants are key facilities for treating urban domestic sewage and industrial wastewater. Their main task is to remove pollutants from sewage and ensure that the effluent quality meets the discharge standards or reaches the standards for reuse. Sewage quality fluctuates over time and seasonal changes, and this change will have a significant impact on the treatment capacity and operating costs of sewage treatment plants. Therefore, in order to ensure that sewage treatment plants can operate economically and efficiently, it is necessary to develop an operating cost optimization method. This method aims to effectively reduce costs through reasonable planning and management while maintaining sewage treatment effects to ensure that sewage treatment plants operate economically and efficiently.

[0081] In the existing technology, the optimization of sewage treatment plant operating costs usually focuses on the optimization of the operating rules of a single or multiple pumping stations, but these methods do not fully consider the impact of pumping station operation on the final effluent water quality. Although the optimization of the internal process energy consumption of the sewage treatment plant can effectively reduce the operating cost of the sewage treatment plant itself, this does not involve the control and optimization of the water quality of the front-end pipe network. Therefore, the current technical methods fail to comprehensively consider and optimize the operating costs of sewage treatment plants from the source to the end of the treatment process.

[0082] However, the existing technology has some shortcomings in optimizing the operating costs of sewage treatment plants. First, when optimizing costs, the existing technology does not fully take into account the impact of water quality changes on costs, and ignores the direct impact of water quality factors on sewage treatment costs. Secondly, the existing technology lacks a comprehensive plant-network coordination mechanism to control costs, that is, the sewage treatment plant and the entire sewage collection and transportation network are not optimized as a whole. In addition, the existing optimization process relies heavily on manual experience and intuition, which is not only inefficient, but also may lead to unnecessary increases in operating costs. In general, the existing technology needs a more scientific and systematic approach to achieve cost optimization of sewage treatment plants in order to improve efficiency and reduce costs.

[0083] In response to the above problems, this application proposes a method for optimizing the operating costs of sewage treatment plants. This method optimizes the operating costs of sewage treatment plants by comprehensively considering the impact of water quality changes on costs, achieving cost control for coordinated operation of plants and networks, and reducing reliance on manual experience, thereby ensuring that sewage treatment plants can operate more economically and efficiently.

[0084] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0085] Figure 1 A schematic diagram of a method for optimizing the operating costs of a sewage treatment plant provided for an application example Figure 1 .like Figure 1 As shown, the method for optimizing the operating cost of a sewage treatment plant provided in this embodiment includes:

[0086] S101. Obtain basic data of the sewage treatment plant, and determine corresponding operation rule parameters based on the basic data.

[0087] Among them, real-time and historical basic data of sewage treatment plants are obtained by installing online monitoring equipment, manual sampling and analysis, etc., including: user sewage discharge coefficient, daily discharge pattern, sewage pipe network, pump station basic data, sewage pump station operation rules, pump station scheduling cost calculation data, sewage treatment plant inlet and outlet water quality data, sewage treatment cost accounting data, etc.

[0088] Based on the basic data, the collected data is sorted, the water quality change patterns and cost structure are analyzed, the patterns and trends in the data are identified, and the corresponding operating rule parameters are determined.

[0089] One possible implementation method is to collect the basic data of the sewage treatment plant as listed in Table 1, and determine the corresponding operation rule parameters based on the basic data in Table 1:

[0090] Table 1

[0091]

[0092] By obtaining the basic data of the sewage treatment plant and determining the operating rule parameters based on these data, and by reasonably adjusting the operating parameters, the treatment efficiency and stability of the sewage treatment plant can be improved.

[0093] S102. Input basic data and operation rule parameters into the pipe network model to obtain the objective function value of the sewage treatment plant.

[0094] Among them, the pipe network model of the sewage treatment plant is constructed based on the basic data to ensure that the model can accurately reflect the actual sewage flow and treatment process. The basic data and operation rule parameters are input into the pipe network model, such as the sewage treatment plant's inlet conditions, treatment process parameters, pump station scheduling rules, etc. The operation pipe network model simulates the water quality treatment process of the sewage treatment plant, and observes the sewage treatment plant's inlet water quality, treatment efficiency and effluent water quality under different operation rules. According to the simulation results, the variable costs of the sewage treatment plant are calculated, such as electricity costs, drug consumption, etc. The objective function is constructed, and the objective function value of the sewage treatment plant is calculated based on the calculated variable cost of the sewage treatment plant. The objective function value reflects the operating cost of the sewage treatment plant under the current operation rules. By evaluating the impact of different operation rules on the objective function value, the most cost-effective operation strategy can be identified.

[0095] By inputting basic data and operating rule parameters into the pipe network model, the objective function value is obtained. The operating cost of the sewage treatment plant can be effectively evaluated through the objective function value, thereby achieving beneficial effects such as cost savings, water quality compliance, and improved operating efficiency.

[0096] S103. When the objective function value does not satisfy the preset conditions, the operation rule parameters are updated, and a new objective function value is determined based on the new operation rule parameters until the objective function value satisfies the preset conditions.

[0097] Among them, after the pipe network model runs and simulates, the objective function value under the current operating rules is evaluated, and the objective function value represents the operating cost of the sewage treatment plant. The preset conditions of the objective function value are determined, such as: the percentage of cost reduction or a specific cost threshold, as the optimization standard. It is judged whether the current objective function value meets the preset conditions, that is, whether the algorithm converges.

[0098] When the objective function value does not meet the preset conditions, for example, the particle swarm algorithm is used to adjust the operating rule parameters, the updated operating rule parameters are input into the model, the simulation is re-performed, and the new objective function value is calculated. Repeat the above steps, through continuous iteration, gradually optimize the operating rules until the objective function value meets the preset conditions.

[0099] The optimal operation rule and the corresponding objective function value are recorded in each iteration. The change range of the objective function value in consecutive iterations is checked. If the change range is less than the set threshold, the algorithm is considered to have converged. Once the objective function value meets the preset conditions, the final operation rule parameters are determined.

[0100] By continuously updating the operating rule parameters and calculating the new objective function value until the objective function value meets the preset conditions, the final operating rule parameters are determined. This can effectively reduce the operating costs of the sewage treatment plant, improve operating efficiency, ensure that water quality meets standards, and achieve the goal of sustainable operation.

[0101] S104. Obtain target operating rule parameters in the pipe network model, where the target operating rule parameters are operating rule parameters corresponding to when the objective function value meets a preset condition.

[0102] Among them, the target operation rule parameters in the pipe network model are obtained. The target operation rule parameters are optimized target operation rule parameters. The target operation rule parameters correspond to the operation rule parameters when the objective function value at this time meets the preset conditions. The optimized target operation rule parameters are applied to actual operations, and the operating cost of the sewage treatment plant is optimal.

[0103] By obtaining the target operating rule parameters in the pipe network model, that is, the operating rule parameters corresponding to the objective function value when the preset conditions are met, and applying the target operating rule parameters to actual operations, the operating cost of the sewage treatment plant can be effectively reduced, the operating efficiency can be improved, the water quality can be ensured to meet the standards, and the goal of sustainable operation can be achieved.

[0104] This embodiment proposes a method for optimizing the operating cost of a sewage treatment plant. The method obtains basic data of the sewage treatment plant and determines corresponding operating rule parameters based on the basic data; inputs the basic data and the operating rule parameters into a pipe network model to obtain an objective function value of the sewage treatment plant, where the objective function value is used to indicate the operating cost of the sewage treatment plant; when the objective function value does not meet a preset condition, the operating rule parameters are updated, and based on the new operating rule parameters, a new objective function value is determined until the objective function value meets the preset condition; obtains the target operating rule parameters in the pipe network model, where the target operating rule parameters are the operating rule parameters corresponding to the objective function value when the preset condition is met, and the operating cost of the sewage treatment plant corresponding to the target operating rule parameters is optimal, thereby reducing the operating cost and improving the economic benefit.

[0105] Figure 2 This is a schematic diagram of a method for optimizing the operating costs of a sewage treatment plant provided in an embodiment of the present application. Figure 2 This embodiment is in Figure 1 Based on the examples, the method for optimizing the operating cost of a sewage treatment plant is described in detail. Figure 2 As shown, the method for optimizing the operating cost of a sewage treatment plant provided in this embodiment includes:

[0106] S201. Obtain basic data of a sewage treatment plant and determine regional distribution information of the sewage treatment plant. The regional distribution information includes: multiple drainage areas.

[0107] Among them, real-time and historical basic output of sewage treatment plants is collected by installing online monitoring equipment and manual sampling and analysis, such as: geographic information, population density, inlet and outlet water quality data, processing capacity, energy consumption data, operating costs and other basic information.

[0108] Investigate the geographical area served by the sewage treatment plant and determine the distribution of drainage areas. Divide the service area into multiple drainage areas based on factors such as sewage pipe network layout, user distribution, topography, etc.

[0109] S202. For any one of the plurality of drainage areas, the pipes in the drainage area are merged according to the plurality of pipes and the plurality of pumping stations to obtain an association relationship between the merged pipes and the pumping stations.

[0110] Among them, for any one of the multiple drainage areas, data integration and analysis are carried out on the sewage generation, water quality characteristics, discharge patterns, etc. of each drainage area.

[0111] Collect information about all pipes in the drainage area, such as the location, diameter, length, etc. of the pipes; collect information about all pumping stations in the drainage area, such as the location, power, efficiency, etc. of the pumping stations; analyze the connection between pipes and pumping stations, such as which pipes are connected to a specific pumping station. Perform similarity analysis on multiple pipes in the drainage area to identify groups of pipes with similar characteristics. Based on the results of the similarity analysis, formulate principles for pipe merging. Based on the merging principles, similar pipes are merged to obtain the association between the merged pipes and pumping stations, thereby simplifying the pipe network structure.

[0112] By merging multiple pipes in the drainage area and obtaining the association between the merged pipes and pump stations, the pipe network structure can be effectively simplified, the amount of data processed by the model can be reduced, and the model processing efficiency can be improved.

[0113] S203: Determine corresponding operation rule parameters according to basic data and association relationships.

[0114] S204: Based on the operation rule parameters, the model parameters of the pipe network model are updated.

[0115] Among them, the collected basic data, including sewage discharge, water quality parameters, pump station operation data, etc., are analyzed in depth. The relationship between pipelines, pump stations and sewage treatment plants, as well as their impact on water quality and quantity, are clarified. According to the basic data and the relationship, the pump station operation rule parameters are determined, such as operation time, start and stop frequency, pump station scheduling strategy, etc. Based on the operation rule parameters, the operation rule parameters are mapped to the pipe network model, and the model parameters of the pipe network model are updated.

[0116] S205. Control the updated pipe network model to simulate the water quality change process of the sewage treatment plant according to the basic data to obtain prediction data output by the pipe network model.

[0117] The collected basic data such as sewage discharge data, pipe network characteristics, pump station operation information, etc. are input into the updated model. The updated pipe network model is controlled to simulate the water quality change process of the sewage treatment plant in the future according to the basic data to obtain the predicted data output by the pipe network model, such as water quality change trend, flow change, etc.

[0118] By simulating the water quality change process of the updated pipe network model and obtaining the predicted data output by the pipe network model, the results of water quality changes after water quality treatment can be understood.

[0119] S206: Compare the predicted data with the actual test data to determine the performance index of the pipe network model.

[0120] The actual water quality test data of the sewage treatment plant during the simulation period, such as BOD5, SS, TN and other water quality data, are collected to compare the model prediction data with the actual test data, and analyze the consistency and deviation between the two. According to the deviation between the model prediction data and the actual test data quality inspection, the performance indicators of the pipe network model are determined, such as Nash efficiency coefficient, root mean square error, or mean absolute error.

[0121] By comparing the predicted data with the actual test data, the performance indicators of the pipeline network model are determined, the performance indicators are analyzed, the advantages and disadvantages of the pipeline network model are identified, and the prediction accuracy of the model is effectively improved.

[0122] S207. When the performance index is greater than a preset value, the predicted data is determined to be hydraulic parameters of the target sewage treatment plant, and the inlet water quality parameters of the target sewage treatment plant are determined based on the hydraulic parameters.

[0123] When the performance index is greater than the preset value, it is considered that the prediction accuracy of the pipe network model meets the requirements. The prediction data that meets the performance index requirements are used as the hydraulic parameters of the target sewage treatment plant, and the inlet water quality parameters of the target sewage treatment plant are predicted based on the hydraulic parameters.

[0124] By determining the hydraulic parameters of the target sewage treatment plant when the performance index is greater than the preset value, and determining the inlet water quality parameters based on the hydraulic parameters, the accuracy of the inlet water quality parameters can be effectively improved, thereby providing more accurate decision support for the optimization of the operating cost of the sewage treatment plant.

[0125] S208. Determine the concentration value of the target indicator according to the inlet water quality parameters, and determine the objective function value of the sewage treatment plant according to the concentration value of the target indicator.

[0126] Among them, according to the treatment objectives and emission standards of the sewage treatment plant, select the target indicators that need to be controlled, for example: the target indicator concentration value is used to indicate the content of organic pollutants in the water body of the sewage treatment plant. Specifically, according to the water quality parameters entering the plant, the concentration value of organic pollutants in the water body of the sewage treatment plant is determined.

[0127] S209: When the objective function value does not satisfy the preset conditions, the operation rule parameters are updated, and a new objective function value is determined based on the new operation rule parameters until the objective function value satisfies the preset conditions.

[0128] Among them, when the objective function value does not meet the preset conditions, that is, when the objective function value does not converge, the operating rule parameters are updated. After the operating rule parameters change, the sediment transport efficiency of the sewage treatment plant will be affected, and then the inlet water quality of the sewage treatment plant will be affected.

[0129] One possible implementation method is to update the operating rule parameters through the particle swarm optimization algorithm to optimize the pump station scheduling and reduce the operating cost of the sewage treatment plant.

[0130] Considering a single pump station as a particle, its velocity update equation is as follows:

[0131]

[0132]

[0133] in, is the particle update speed, is the current velocity of the particle, is the current position of the particle, is the updated position, , The learning factor can refer to the influence of the particle optimal solution and the global optimal solution. , A random number between (0,1) can prevent premature convergence. is the optimal solution of the ith particle in the lth time period, is the optimal solution of the global particle within the time l experienced. The particle position contains two dimensions, namely the operation time of the pump station and the change in the frequency of pump station start and stop. Its change range and initial change speed can be determined according to the actual situation. The updated model parameters are rewritten, including the start and stop time of the pump station, the number of pump stations opened, etc.

[0134] If the global optimal solution If the condition remains unchanged or changes very little in multiple consecutive iterations, it can be used as a sign of objective function convergence, and the iteration process will end. If the condition is not met, the operating rule parameters are updated, and a new round of calculations is performed based on the new operating rule parameters to determine the new objective function value.

[0135] S210. Obtain target operating rule parameters in the pipe network model, where the target operating rule parameters are operating rule parameters corresponding to when the objective function value meets a preset condition.

[0136] Step S210 is the same as step S104 and will not be described again.

[0137] This embodiment proposes a method for optimizing the operating cost of a sewage treatment plant. The method collects basic data of the sewage treatment plant, divides the drainage area, simplifies the pipe network structure, sets the operating rule parameters, and updates the model to simulate water quality changes. Through model performance evaluation, hydraulic and water quality parameters are determined, and the objective function value is calculated and optimized. Finally, iterative adjustments are made until the preset conditions are met, and the optimal operating rule parameters are obtained to achieve the optimization of the cost and efficiency of the sewage treatment plant.

[0138] Figure 3 This is a schematic diagram of a method for optimizing the operating costs of a sewage treatment plant provided in an embodiment of the present application. Figure 3 This embodiment is in Figure 1 Based on the embodiment, a possible implementation method of determining the objective function value of a sewage treatment plant according to the concentration value of the target indicator is described in detail. Figure 3 As shown, the method for optimizing the operating cost of a sewage treatment plant provided in this embodiment includes:

[0139] S301. According to the water quality parameters entering the plant, sediment simulation treatment is performed to determine the suspended solids concentration of the sewage in the sewage treatment plant.

[0140] Among them, according to the water quality parameters entering the plant, select appropriate mathematical models or simulation software to simulate sediments, analyze the physical and chemical characteristics of sediments in sewage, and understand their distribution and behavior in sewage. According to the simulation results, the suspended solids concentration of sewage in the sewage treatment plant is determined.

[0141] By conducting sediment simulation treatment based on the inlet water quality parameters and determining the suspended solids concentration in the sewage treatment plant, data support is provided for the subsequent calculation of the operating costs of the sewage treatment plant.

[0142] One possible implementation method is that sediment simulation treatment does not take into account the erosion, transport and deposition processes of sediments. It is necessary to couple the sediment motion equation to further improve the sediment simulation function. According to the inlet water quality parameters, sediment simulation treatment is carried out to determine the suspended solids concentration of the sewage in the sewage treatment plant.

[0143] S302. Determine the target concentration value of the sewage treatment plant according to the suspended solids concentration.

[0144] Among them, the target indicator concentration value of the sewage treatment plant is determined according to the suspended solids concentration, and the target indicator concentration value is used to indicate the content of organic pollutants in the water body of the sewage treatment plant.

[0145] In one possible implementation, the suspended solids concentration of the sewage transported by the sediment is approximately 0.7 to 1.0 times that of Concentration. The concentration of suspended solids in the water of the sewage treatment plant is determined based on the multiple relationship between the suspended solids concentration of sewage and the concentration of organic pollutants. concentration.

[0146] S303. Determine the unit electricity consumption cost of the sewage treatment plant according to the total nitrogen value and the target indicator concentration value in the inlet water quality parameters.

[0147] The electricity cost of the sewage treatment plant mainly includes the electricity consumption of aeration, sewage pump lifting, return, mixing and desludging. The electricity consumption cost is different under different water quality conditions. The unit electricity consumption cost of the sewage treatment plant is calculated based on the total nitrogen value and target indicator concentration value in the water quality parameters entering the plant.

[0148] A possible implementation method is to determine the total nitrogen (TN) value and target index in the water quality parameters entering the plant. Concentration value, and according to the total nitrogen value TN and target index Concentration value, determine the unit electricity consumption cost of the sewage treatment plant.

[0149] Specifically, for example, the total nitrogen (TN) value in the incoming water quality parameters is 30 mg / L, and the target index is The concentration value is 75 mg / L. According to Table 2, it can be determined that the unit electricity consumption cost of the sewage treatment plant is 0.165 yuan.

[0150] Table 2 is a table of electricity costs under different influent water quality conditions provided in this embodiment:

[0151] Table 2

[0152]

[0153] S304. Determine the unit chemical consumption cost of the sewage treatment plant according to the total nitrogen value and the target indicator concentration value in the inlet water quality parameters.

[0154] Among them, the main components of the sewage treatment plant's drug consumption cost include chemical phosphorus removal, carbon source addition, sludge treatment conditioning agents and disinfectants. The drug consumption cost under different water quality conditions is different. The unit drug consumption cost of the sewage treatment plant is calculated based on the total nitrogen value and target indicator concentration value in the inlet water quality parameters.

[0155] A possible implementation method is to determine the total nitrogen (TN) value and target index in the water quality parameters entering the plant. Concentration value, and according to the total nitrogen value TN and target index Concentration value determines the unit chemical consumption cost of the sewage treatment plant.

[0156] Specifically, for example, the total nitrogen (TN) value in the incoming water quality parameters is 30 mg / L, and the target index is The concentration value is 75 mg / L. According to Table 2, it can be determined that the unit electricity consumption cost of the sewage treatment plant is 0.234 yuan.

[0157] Table 3 is a table of drug cost under different influent water quality conditions provided in this embodiment:

[0158] Table 3

[0159]

[0160] S305. Determine the operating cost of the sewage treatment plant according to the unit electricity consumption cost and the unit chemical consumption cost.

[0161] Among them, the operating cost of the sewage treatment plant is determined based on the unit electricity consumption cost and the unit drug consumption cost. Specifically, the dimensionless operating cost of the sewage treatment plant is calculated using the following company: :

[0162]

[0163] in, is the dimensionless sewage treatment plant operating cost of the yth water plant, is the operating cost of the sewage treatment plant under the current water quality, The operating cost of the sewage treatment plant under optimized water quality for sewage treatment plant scheduling.

[0164] A possible implementation method, specifically, the current sewage treatment plant influent The average concentration is 100 mg / L, and the sewage treatment plant influent after pump station scheduling optimization 5 concentration is 75 mg / L, and the average TN concentration is 30 mg / L. According to Table 2 and Table 3, it can be determined that the unit electricity consumption cost under the current water quality is: 0.173, the unit drug consumption cost is: 0.132, and the operating cost of the sewage treatment plant under the current water quality is: According to Table 2 and Table 3, it can be determined that the unit electricity consumption cost of the optimized water quality is: 0.165, the unit drug consumption cost is: 0.234, and the operating cost of the sewage treatment plant under the current water quality .

[0165] Determine the dimensionless operating cost of a sewage treatment plant based on the unit electricity consumption cost and unit chemical consumption cost for: .

[0166] That is, after optimization, the operating cost of the sewage treatment plant is 76% of the cost before optimization, that is, after optimizing the operating rule parameters of the sewage treatment plant, the operating cost of the sewage treatment plant is reduced by 24% compared with before optimization.

[0167] S306. For any one of the multiple pumping stations, the dispatching cost of the sewage treatment plant is calculated according to the operation time of the pumping station and the start and stop frequency of the pumping station.

[0168] Among them, the water pump used in the pump station is a fixed-frequency water pump. When operating in dry weather, the water level change in the forebay of the pump station is relatively small, and the power consumption of the pump per unit time can be roughly regarded as constant. The main factors affecting the cost of the scheduling plan are the daily operation time of the pump station and the start-stop frequency of the pump station. That is, the operating rule parameters are: the operation time of the pump station and the start-stop frequency of the pump station. For any pump station among multiple pump stations, the scheduling cost of the sewage treatment plant is calculated based on the operation time of the pump station and the start-stop frequency of the pump station.

[0169] One possible implementation method is to determine the operating rule parameters of the pump station under different working conditions according to Table 4. The operating rule parameters include: the operating time of the pump station and the start and stop frequency of the pump station.

[0170] Table 4

[0171]

[0172] According to the operation time of the pump station and the start and stop frequency of the pump station, the dimensionless scheduling cost of the sewage treatment plant is calculated using the following formula: :

[0173]

[0174] in, is the dimensionless dispatching cost of the x-th pump station, a and b are the weight coefficients of the pump station operation time and the pump station start and stop, respectively. a is 0.7, b is 0.3. The operating time of the current pump station, The duration used in the dry weather dispatching rules of the pump station, is the current start and stop frequency of the pump station, is the start and stop frequency adopted by the pump station dry weather dispatching rule. =1, with the change of pump station operation time and start-stop frequency Corresponding changes occur.

[0175] S307. Determine the objective function value of the sewage treatment plant according to the operation cost and the scheduling cost.

[0176] Among them, the objective function setting comprehensively considers the operating cost of the sewage treatment plant and the pump station scheduling cost of the sewage treatment plant, among which the weight of the sewage treatment plant operating cost is set larger, and the weight of the pump station scheduling cost is relatively small. Its objective function is:

[0177]

[0178] Among them, w is the pump station dispatch cost weight, x is the number of pump stations, and y is the number of sewage treatment plants. is the dimensionless pump station dispatching cost of the sewage treatment plant, is the dimensionless operating cost of the sewage treatment plant.

[0179] This embodiment proposes a method for optimizing the operating cost of a sewage treatment plant. The method determines the suspended solids concentration of the sewage treatment plant by simulating the water quality parameters entering the plant, reflecting the content of organic pollutants. Based on the suspended solids concentration and the total nitrogen value, the unit power consumption and drug consumption costs are calculated to determine the overall operating cost. At the same time, the dispatching cost is calculated in combination with the operating characteristics of the pump station. Finally, the operating cost and dispatching cost are combined to form an objective function value to optimize the operating efficiency and cost-effectiveness of the sewage treatment plant.

[0180] Figure 4 A schematic diagram of a sewage treatment plant operation cost optimization device provided in this application, such as Figure 4 As shown, the sewage treatment plant operation cost optimization device 400 provided in this embodiment includes:

[0181] The acquisition module 401 is used to acquire basic data of the sewage treatment plant;

[0182] A determination module 402 is used to determine corresponding operation rule parameters based on the basic data;

[0183] The processing module 403 is used to input the basic data and the operating rule parameters into the pipe network model to obtain the objective function value of the sewage treatment plant, and the objective function value is used to indicate the operating cost of the sewage treatment plant;

[0184] The processing module 403 is further configured to update the operation rule parameters when the objective function value does not meet the preset conditions, and determine a new objective function value based on the new operation rule parameters until the objective function value meets the preset conditions, wherein the preset conditions are used to indicate that the objective function value converges;

[0185] The acquisition module 401 is also used to obtain the target operation rule parameters in the pipe network model, the target operation rule parameters are the operation rule parameters corresponding to the objective function value when the preset conditions are met, and the sewage treatment plant operation cost corresponding to the target operation rule parameters is optimal.

[0186] Optionally, the processing module 403 is further used to control the pipe network model to simulate the water quality changes of the sewage treatment plant based on the basic data and the operation rule parameters to obtain corresponding inlet water quality parameters;

[0187] The determination module 402 is further used to determine the concentration value of the target indicator according to the inlet water quality parameter, and determine the objective function value of the sewage treatment plant according to the concentration value of the target indicator.

[0188] Optionally, the determination module 402 is further used to determine the regional distribution information of the sewage treatment plant, and the regional distribution information includes: a plurality of drainage areas;

[0189] The processing module 403 is further used to merge the pipes in any one of the plurality of drainage areas according to the plurality of pipes and the plurality of pumping stations, and obtain an association relationship between the merged pipes and the pumping stations;

[0190] The determination module 402 is further used to determine corresponding operation rule parameters according to the basic data and the association relationship;

[0191] Optionally, the processing module 403 is further used to update the model parameters of the pipe network model based on the operation rule parameters;

[0192] The processing module 403 is also used to control the updated pipe network model to simulate the water quality changes of the sewage treatment plant based on the basic data to obtain corresponding inlet water quality parameters.

[0193] Optionally, the processing module 403 is further used to control the updated pipe network model to simulate the water quality change process of the sewage treatment plant according to the basic data to obtain the prediction data output by the pipe network model;

[0194] The determination module 402 is further used to compare the predicted data with the actual detection data to determine the performance index of the pipe network model;

[0195] The determination module 402 is further configured to determine, when the performance indicator is greater than a preset value, that the predicted data is a hydraulic parameter of the target sewage treatment plant, and determine an inlet water quality parameter of the target sewage treatment plant according to the hydraulic parameter.

[0196] Optionally, the sewage treatment plant operation cost optimization device further includes: a calculation module 404;

[0197] The determination module 402 is further used to perform sediment simulation processing according to the inlet water quality parameters to determine the suspended solids concentration of the sewage in the sewage treatment plant;

[0198] The determination module 402 is further used to determine a target indicator concentration value of the sewage treatment plant according to the suspended solids concentration, wherein the target indicator concentration value is used to indicate the content of organic pollutants in the water body of the sewage treatment plant;

[0199] The calculation module 404 is used to calculate the operation cost of the sewage treatment plant according to the target indicator concentration value;

[0200] The determination module 402 is further configured to determine an objective function value of the operating cost of the target sewage treatment plant according to the operating cost.

[0201] Optionally, the determination module 402 is further used to determine the unit electricity consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value;

[0202] The determination module 402 is further used to determine the unit drug consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value;

[0203] The determination module 402 is further configured to determine the operation cost of the sewage treatment plant according to the unit electricity consumption cost and the unit drug consumption cost.

[0204] Optionally, the calculation module 404 is further used to calculate the scheduling cost of the sewage treatment plant for any one of the multiple pumping stations according to the operation time of the pumping station and the start and stop frequency of the pumping station;

[0205] The determination module 402 is further configured to determine the objective function value of the sewage treatment plant according to the operation cost and the scheduling cost.

[0206] Figure 5 The schematic diagram of the structure of the sewage treatment plant operation cost optimization equipment provided for this application. Figure 5 As shown, the present application provides a sewage treatment plant operating cost optimization device, and the edge node security application scheduling device 500 includes: a receiver 501, a transmitter 502, a processor 503 and a memory 504.

[0207] Receiver 501, used for receiving instructions and data;

[0208] A transmitter 502, used for sending instructions and data;

[0209] Memory 504, used to store computer-executable instructions;

[0210] The processor 503 is used to execute the computer-executable instructions stored in the memory 504 to implement the various steps performed by the method for optimizing the operating cost of a sewage treatment plant in the above embodiment. For details, please refer to the relevant description in the above embodiment of the method for optimizing the operating cost of a sewage treatment plant.

[0211] Optionally, the memory 504 may be independent or integrated with the processor 503 .

[0212] When the memory 504 is independently provided, the electronic device further includes a bus for connecting the memory 504 and the processor 503 .

[0213] The present application also provides a computer storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, a sewage treatment plant operating cost optimization method as executed by the above-mentioned sewage treatment plant operating cost optimization device is implemented.

[0214] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware implementations, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0215] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0216] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for optimizing the operating cost of a sewage treatment plant, characterized in that: The method comprises: Obtaining basic data of the sewage treatment plant, and determining corresponding operating rule parameters based on the basic data; Inputting the basic data and the operating rule parameters into a pipe network model to obtain an objective function value of the sewage treatment plant, wherein the objective function value is used to indicate the operating cost of the sewage treatment plant; In the case where the objective function value does not meet the preset condition, the operation rule parameter is updated, and a new objective function value is determined based on the new operation rule parameter until the objective function value meets the preset condition, wherein the preset condition is used to indicate that the objective function value converges; The target operation rule parameters in the pipe network model are obtained, where the target operation rule parameters are operation rule parameters corresponding to when the objective function value meets preset conditions, and the sewage treatment plant operation cost corresponding to the target operation rule parameters is optimal.

2. The method according to claim 1, characterized in that The step of inputting the basic data and the operating rule parameters into the pipe network model to obtain the objective function value of the sewage treatment plant includes: Controlling the pipe network model to simulate the water quality changes of the sewage treatment plant based on the basic data and the operation rule parameters to obtain corresponding inlet water quality parameters; According to the inlet water quality parameter, the concentration value of the target indicator is determined, and according to the concentration value of the target indicator, the objective function value of the sewage treatment plant is determined.

3. The method according to claim 2, characterized in that The basic data includes: a plurality of pipelines and a plurality of pumping stations, and the corresponding operation rule parameters are determined based on the basic data, including: Determining regional distribution information of the sewage treatment plant, the regional distribution information comprising: a plurality of drainage areas; For any one of the plurality of drainage areas, according to the plurality of pipelines and the plurality of pumping stations, the pipelines in the drainage area are merged to obtain an association relationship between the merged pipelines and the pumping stations; Determine corresponding operation rule parameters according to the basic data and the association relationship; The controlling of the pipe network model simulates the water quality changes of the sewage treatment plant based on the basic data and the operation rule parameters to obtain corresponding inlet water quality parameters, including: Based on the operating rule parameters, updating the model parameters of the pipe network model; The updated pipe network model is controlled to simulate the water quality changes of the sewage treatment plant based on the basic data to obtain corresponding inlet water quality parameters.

4. The method according to claim 3, characterized in that The updated pipe network model is controlled to simulate the water quality changes of the sewage treatment plant based on the basic data to obtain corresponding inlet water quality parameters, including: Controlling the updated pipe network model to simulate the water quality change process of the sewage treatment plant according to the basic data to obtain the prediction data output by the pipe network model; Comparing the predicted data with the actual detection data to determine the performance index of the pipe network model; When the performance indicator is greater than a preset value, the predicted data is determined to be the hydraulic parameters of the target sewage treatment plant, and the inlet water quality parameters of the target sewage treatment plant are determined based on the hydraulic parameters.

5. The method according to claim 2, characterized in that: Determining the concentration value of the target indicator according to the inlet water quality parameter, and determining the objective function value of the sewage treatment plant according to the concentration value of the target indicator, includes: According to the inlet water quality parameters, sediment simulation treatment is performed to determine the suspended solids concentration of the sewage in the sewage treatment plant; Determining a target indicator concentration value of the sewage treatment plant according to the suspended solids concentration, wherein the target indicator concentration value is used to indicate the content of organic pollutants in the water body of the sewage treatment plant; Calculating the operating cost of the sewage treatment plant according to the target indicator concentration value; The objective function value of the target sewage treatment plant operating cost is determined according to the operating cost.

6. The method according to claim 5, characterized in that The calculating the operating cost of the sewage treatment plant according to the target indicator concentration value includes: Determining the unit electricity consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value; Determining the unit drug consumption cost of the sewage treatment plant according to the total nitrogen value in the inlet water quality parameter and the target indicator concentration value; The operating cost of the sewage treatment plant is determined according to the unit electricity consumption cost and the unit drug consumption cost.

7. The method according to claim 5, characterized in that The operating rule parameters include: the operating time of the pump station and the start and stop frequency of the pump station. The objective function value of the target sewage treatment plant operating cost determined according to the operating cost includes: For any one of the plurality of pumping stations, calculating the dispatching cost of the sewage treatment plant according to the operation time of the pumping station and the start and stop frequency of the pumping station; The objective function value of the sewage treatment plant is determined according to the operating cost and the scheduling cost.

8. A sewage treatment plant operation cost optimization device, characterized in that: The device comprises: Acquisition module, used to obtain basic data of sewage treatment plants; A determination module, used to determine corresponding operation rule parameters based on the basic data; A processing module, used for inputting the basic data and the operating rule parameters into a pipe network model to obtain an objective function value of the sewage treatment plant, wherein the objective function value is used to indicate the operating cost of the sewage treatment plant; The processing module is further configured to update the operation rule parameters if the objective function value does not meet the preset conditions, and determine a new objective function value based on the new operation rule parameters until the objective function value meets the preset conditions, wherein the preset conditions are used to indicate that the objective function value converges; The acquisition module is also used to obtain the target operation rule parameters in the pipe network model, the target operation rule parameters are the operation rule parameters corresponding to the objective function value when the preset conditions are met, and the sewage treatment plant operation cost corresponding to the target operation rule parameters is optimal.

9. A sewage treatment plant operation cost optimization device, characterized in that: include: Memory; processor; Wherein, the memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method for optimizing the operating cost of a sewage treatment plant according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that: The computer storage medium stores computer execution instructions, which, when executed by a processor, are used to implement the method for optimizing the operating cost of a sewage treatment plant according to any one of claims 1 to 7.

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