Optimization method of water supply network, equipment and medium

Abstract

The invention discloses a water supply network optimization method and device and a medium, and the method comprises the steps: collecting the pipeline information of a water supply network in a target city through a geographic information system; determining model parameters according to the pipeline information, constructing an initial hydraulic model based on the model parameters, and simplifying the initial hydraulic model through a simplification principle algorithm to obtain a simplified hydraulic model; the method comprises the following steps: collecting dynamic pipeline data in a water supply network pipeline in real time through an Internet of Things system, and simulating a water flow operation condition of a pipeline of a target city through a simplified hydraulic model according to the dynamic pipeline data; simulation errors are obtained, model parameters are adjusted based on the simulation errors until the simplified hydraulic model converges, and a mature hydraulic model is obtained; and optimizing the water supply network pipeline through the mature hydraulic model. By building the hydraulic model, errors caused by original data errors or human errors in the model building process can be eliminated to the maximum extent.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent control of water supply pipe networks, and specifically to an optimization method, equipment and medium for water supply pipe networks. Background Art

[0002] With the growing demand for water in cities, the requirements for water quality and safety are becoming higher and higher, and the optimization of water resource allocation is becoming more and more important. Since the construction of urban water supply networks is long and continuous, urban water supply networks contain a large number of pipes, pumping stations, valves, water towers and other elements with different pipe materials, different pipe diameters and different laying years. These elements not only reflect the precipitation of history, but also determine that the water supply network system has become a comprehensive system with extremely complex topological structure and highly variable operating conditions.

[0003] Nowadays, the construction of urban water supply pipelines usually requires manual measurement of data, which is prone to errors caused by data errors or human mistakes. Summary of the invention

[0004] In order to solve the above problems, this application proposes a method for optimizing a water supply network, including:

[0005] Collect pipeline information of the water supply network in the target city through a geographic information system, wherein the pipeline information includes basic pipeline information, pipeline node information, water pump information and geographic information;

[0006] Determine model parameters according to the pipeline information, construct an initial hydraulic model based on the model parameters, and simplify the initial hydraulic model by using a simplification principle algorithm to obtain a simplified hydraulic model;

[0007] The dynamic pipeline data in the water supply network pipeline is collected in real time through the Internet of Things system, and the water flow operation status of the pipeline in the target city is simulated through the simplified hydraulic model according to the dynamic pipeline data;

[0008] Comparing the simulated water flow data output by the simplified hydraulic model with the actual water flow data to obtain a simulation error, and adjusting the model parameters based on the simulation error until the simplified hydraulic model converges to obtain a mature hydraulic model;

[0009] The water supply network pipeline is optimized through the mature hydraulic model.

[0010] On the other hand, the present application also proposes an optimization device for a water supply network, comprising:

[0011] at least one processor; and,

[0012] a memory communicatively connected to the at least one processor; wherein,

[0013] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a water supply network optimization method as described in the above example.

[0014] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as: a method for optimizing a water supply network as described in the above example.

[0015] The present application proposes a water supply network optimization method which can bring the following beneficial effects:

[0016] According to the simulation of water supply network, the hydraulic model platform can eliminate the errors caused by original data errors or human errors in the model creation process to the greatest extent through a series of complete mass data and attribute data inspection and error correction processes, thereby ensuring that the topological characteristics of the model can accurately conform to the actual situation. The hydraulic model is dynamically calibrated according to the pump operation curve and node flow, pressure and other monitoring data to effectively reduce the deviation of the simulation data, so that the simulation effect can accurately reflect the changes in the hydraulic parameters of the real pipe network. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0018] Figure 1 A schematic diagram of a flow chart of a method for optimizing a water supply network in an embodiment of the present application;

[0019] Figure 2 This is a schematic diagram of an optimization device for a water supply network in an embodiment of the present application. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0021] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0022] like Figure 1 As shown, the embodiment of the present application provides a method for optimizing a water supply network, comprising:

[0023] S101: Collecting pipeline information of the water supply network in the target city through a geographic information system, wherein the pipeline information includes basic pipeline information, pipeline node information, water pump information and geographic information.

[0024] Specifically, through on-site investigation, measurement and recording, detailed information of water supply pipelines is collected, including the location, material, diameter, burial depth, etc. of the pipelines. The collected detailed information of water supply pipelines is entered into the GIS system for digital processing, and the digitally processed detailed information of water supply pipelines is corrected to make it more in line with the actual situation.

[0025] Furthermore, according to the corrected water supply pipeline detailed information, the pipeline information of the water supply network is obtained, and the pipeline information includes basic pipeline information, pipeline node information, water pump information and geographic information.

[0026] Among them, the basic information of the pipeline includes pipeline material information, pipeline diameter information, pipeline usage information, etc.; the pipeline node information includes node location, node type (such as water plant, pipe section intersection, etc.), etc.; the water pump information includes water pump location, water pump performance, etc.; the geographic information includes the pipeline geographical coordinates, topography, surrounding environment, administrative divisions, etc.

[0027] S102: Determine model parameters according to the pipeline information, construct an initial hydraulic model based on the model parameters, and simplify the initial hydraulic model through a simplification principle algorithm to obtain a simplified hydraulic model.

[0028] Specifically, the diameter, material, length, wall thickness, roughness and other parameters in the hydraulic model are determined according to the basic information of the pipeline; the pipeline node position, pipeline connection, pipeline distribution and other parameters in the hydraulic model are determined according to the pipeline node information; the power and position of the water pump model in the hydraulic model are determined according to the water pump information; the geographic coordinates, terrain elevation, soil type and other parameters of the pipeline in the hydraulic model are determined according to the geographic information, and the initial hydraulic model is constructed based on the determined model parameters.

[0029] Furthermore, according to the influence of each node in the water supply network pipeline on the water supply performance (such as flow distribution and pressure demand), the key pipeline nodes and non-critical pipeline nodes in the water supply network pipeline are determined, and the key pipeline node parameters corresponding to the key pipeline nodes in the initial hydraulic model and the non-critical pipeline node parameters corresponding to the non-critical pipeline nodes in the initial hydraulic model are determined.

[0030] According to the preset algorithms corresponding to the macro-equivalence principle and the small error principle, the parameters of non-critical pipeline nodes are simplified, and the parameters of critical pipeline nodes are kept unchanged to obtain a simplified hydraulic model, so as to keep the overall performance of the hydraulic model (such as total flow, total pressure loss, etc.) unchanged or approximately unchanged.

[0031] It should be noted that critical pipeline nodes are usually those that have a significant impact on the overall performance of the hydraulic model or are located on the critical path of the hydraulic model, such as the entrance of a large pump station, an important user connection point, the lowest pressure point of the hydraulic model, etc. Non-critical pipeline nodes are those that have a small impact on the overall performance of the hydraulic model or are located on the secondary path of the hydraulic model.

[0032] More specifically, the branch nodes in the non-critical pipeline nodes are determined, and the parameters corresponding to the branch nodes are deleted to reduce the complexity and calculation amount of the model. The pipeline intersections of the non-critical pipeline nodes are determined, and the distances between the intersections are obtained. Multiple intersections with distances lower than a preset distance are merged to simplify the model structure of the initial hydraulic model and reduce the number of nodes.

[0033] During the simplification process, the simplified model parameters of the simplified hydraulic model are compared with the initial model parameters of the initial hydraulic model to obtain the simplified error, and judge whether the simplified error is within the preset range. If the simplified error is within the acceptable range, the simplification is considered successful; if the simplified error is too large, it is necessary to adjust the simplification strategy or re-evaluate the preset threshold.

[0034] It should be noted that the branch node usually refers to the node connecting the main pipeline and the smaller branch pipeline. For large-scale urban water supply networks, the simplified water supply network diameter should generally be ≥300mm, which can increase the speed of hydraulic model calculation.

[0035] S103: The dynamic pipeline data in the water supply network pipeline is collected in real time through the Internet of Things system, and the water flow operation status of the pipeline in the target city is simulated through the simplified hydraulic model according to the dynamic pipeline data.

[0036] Specifically, a series of sensors (such as flow sensors, pressure sensors, temperature sensors, etc.) in the Internet of Things (IoT) system collect dynamic pipeline data in the water supply network pipeline in real time. The dynamic pipeline data includes gate opening degree, user water usage information, pipeline monitoring point information, and total water volume of the water supply network. The pipeline monitoring point information includes the flow, pressure, water temperature and other data of the pipeline monitored at the pipeline monitoring point.

[0037] Furthermore, the real-time data of gate opening degree and real-time data of user water consumption collected within the first preset time period are imported into the simplified hydraulic model, and the simulated gate and water flow parameters of the simplified hydraulic model are adjusted. The water flow operation simulation is performed through the simplified hydraulic model to obtain the simulated water flow data of each pipe section of the simplified hydraulic model within the first preset time period. The water flow data include node water pressure, pipe section flow, water source supply pressure, water source supply flow and other data.

[0038] S104: Compare the simulated water flow data output by the simplified hydraulic model with the actual water flow data to obtain a simulation error, and adjust the model parameters based on the simulation error until the simplified hydraulic model converges to obtain a mature hydraulic model.

[0039] Specifically, according to the pipeline monitoring point information, multiple monitoring points in the water supply network monitor the actual water flow data of each pipe section in the water supply network during the first preset time period through multiple monitoring points to obtain the actual water flow data, compare the simulated water flow data with the actual water flow data, and calculate the simulation error of the simplified hydraulic model.

[0040] Further, it is determined whether the simulation error is less than a preset error threshold. If not, the model parameters of the simplified hydraulic model are adjusted, and the simulation is performed again according to the dynamic pipeline data, and the simulation error is calculated again to determine whether the simulation error is less than the preset error threshold, until the simulation error is less than the preset error threshold, it is determined that the simplified hydraulic model has converged; if so, it is determined that the simplified hydraulic model has converged.

[0041] It should be noted that the simulation error can be an absolute error (such as the difference between the simulation value and the actual value) or a relative error (such as the percentage difference between the simulation value and the actual value), and the preset error threshold is set according to the needs and accuracy requirements of the actual application.

[0042] S105: Optimizing the water supply network pipelines through the mature hydraulic model.

[0043] Specifically, when the simplified hydraulic model converges, a mature hydraulic model is obtained, and the water consumption data of each node in the water supply network pipeline is counted within multiple second preset time periods, and the pipe material, pipe diameter and service life of each node in the water supply network pipeline are determined respectively.

[0044] Furthermore, through the simulation based on the water consumption data using a mature hydraulic model, the time period variation coefficient of water consumption corresponding to each node in different time periods is determined to reflect the fluctuation of water consumption in different time periods, which helps to understand the time distribution of water demand. At the same time, the pipe section resistance coefficient of each node in the water supply network pipeline is determined to reflect the degree of obstruction of the pipeline to the flow of water.

[0045] The water supply network pipeline is optimized based on the water consumption time period variation coefficient and the pipe section resistance coefficient.

[0046] Specifically, according to the time period variation coefficient of water consumption, the peak water consumption period and the low water consumption period of each node in the water supply network pipeline are determined. After the peak water consumption period and the low water consumption period of each node are determined, the corresponding water pump needs to be determined for each node.

[0047] When the water consumption is at peak, the power of the water pump is adjusted to the peak range to ensure that there is sufficient water supply capacity to meet the water demand during the peak period. When the water consumption is at low peak, the power of the water pump is adjusted to the low peak range to reduce energy consumption and extend the service life of the water pump. And by adjusting the valves in each pipe in the water supply network pipeline, the pipe section resistance can be further reduced.

[0048] It also includes: according to the information of pipeline monitoring points in the water supply network, determine the specific monitoring point locations, and through these monitoring points, monitor the water pressure of the pipelines in the water supply network in real time to ensure the stable operation of the water supply system. Set a preset water pressure threshold as a standard for judging whether the pipeline water pressure is normal.

[0049] When the pipeline water pressure exceeds the preset water pressure threshold, determine whether the pipeline corresponding to the pipeline water pressure has burst; if not, respond to the water pressure abnormality event and send the water pressure abnormality information to the water pump administrator for abnormal processing. If so, close the valve in the pipeline corresponding to the pipeline water pressure, determine the pipeline position corresponding to the pipeline water pressure, and send the pipeline position to the maintenance department.

[0050] like Figure 2 As shown, the embodiment of the present application also proposes an optimization device for a water supply network, including:

[0051] at least one processor; and,

[0052] a memory communicatively connected to the at least one processor; wherein,

[0053] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a method for optimizing a water supply network as described in any of the above embodiments.

[0054] An embodiment of the present application further provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to be: a method for optimizing a water supply network as described in any of the above embodiments.

[0055] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0056] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0057] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0058] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0061] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0062] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0063] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0064] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0065] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for optimizing a water supply network, characterized in that: include: Collecting pipeline information of the water supply network in the target city through a geographic information system, wherein the pipeline information includes basic pipeline information, pipeline node information, water pump information and geographic information; Determine model parameters according to the pipeline information, construct an initial hydraulic model based on the model parameters, and simplify the initial hydraulic model through a simplification principle algorithm to obtain a simplified hydraulic model; The dynamic pipeline data in the water supply network pipeline is collected in real time through the Internet of Things system, and the water flow operation status of the pipeline in the target city is simulated through the simplified hydraulic model according to the dynamic pipeline data; Comparing the simulated water flow data output by the simplified hydraulic model with the actual water flow data to obtain a simulation error, and adjusting the model parameters based on the simulation error until the simplified hydraulic model converges to obtain a mature hydraulic model; The water supply network pipeline is optimized through the mature hydraulic model.

2. The method for optimizing a water supply network according to claim 1, characterized in that: The simplification of the initial hydraulic model by the simplification principle algorithm to obtain a simplified hydraulic model specifically includes: Determine the key pipeline nodes and non-key pipeline nodes in the water supply network pipeline according to the pipeline node information, and determine the key pipeline node parameters corresponding to the key pipeline nodes in the initial hydraulic model, and the non-key pipeline node parameters corresponding to the non-key pipeline nodes in the initial hydraulic model; The key pipeline node parameters are kept unchanged, and the non-key pipeline node parameters are simplified according to the preset algorithm corresponding to the macro-equivalence principle and the small error principle to obtain a simplified hydraulic model.

3. The method for optimizing a water supply network according to claim 2, characterized in that: The algorithm corresponding to the preset macro-equivalence principle and the small error principle is used to simplify the non-critical pipeline node parameters, specifically including: Determine a branch node among the non-critical pipeline nodes, and delete parameters corresponding to the branch node; and determining the pipeline intersections of the non-critical pipeline nodes, obtaining the distances between the intersections, and merging a plurality of intersections whose distances are less than a preset distance to simplify the model structure of the initial hydraulic model; During the simplification process, the simplified model parameters of the simplified hydraulic model are compared with the initial model parameters of the initial hydraulic model to obtain a simplified error, and it is determined whether the simplified error is within a preset range.

4. The method for optimizing a water supply network according to claim 1, characterized in that: The dynamic pipeline data includes gate opening degree, user water use information, pipeline monitoring point information, and total water volume of the water supply network; The simulating of the water flow operation status of the pipeline of the target city by the simplified hydraulic model according to the dynamic pipeline data specifically includes: Importing the real-time data of the gate opening degree and the real-time data of user water consumption collected within the first preset time period into the simplified hydraulic model, adjusting the simulated gate and water flow parameters of the simplified hydraulic model, and performing water flow operation simulation through the simplified hydraulic model; The simulated water flow data of each pipe section of the simplified hydraulic model within the first preset time period is obtained, wherein the water flow data includes node water pressure, pipe section flow, water source water supply pressure, and water source water supply flow.

5. A method for optimizing a water supply network according to claim 4, characterized in that: The comparing the simulated water flow data with the actual water flow data to obtain a simulation error, and adjusting the model parameters based on the simulation error specifically includes: Determining actual water flow data of each pipe section in the water supply network within the first preset time period according to the pipeline monitoring point information; Comparing the simulated water flow data with the actual water flow data, determining a simulation error of the simplified hydraulic model, and judging whether the simulation error is less than a preset error threshold; If not, adjusting the model parameters of the simplified hydraulic model and performing simulation again according to the dynamic pipeline data; If so, it is determined that the simplified hydraulic model has converged.

6. The method for optimizing a water supply network according to claim 1, characterized in that: The basic information of the pipeline includes pipeline material information, pipeline diameter information, and pipeline usage information; The optimizing of the water supply network pipeline by the mature hydraulic model specifically includes: In a plurality of second preset time periods, the water consumption data of each node in the water supply network pipeline is counted, and the pipe material, pipe diameter and service life of each node in the water supply network pipeline are determined; Through the mature hydraulic model, simulation is performed based on the water consumption data to determine the water consumption time period variation coefficient corresponding to each node in different time periods, as well as the pipe section resistance coefficient of each node in the water supply network pipeline. According to the water consumption time period variation coefficient and the pipe section resistance coefficient, the water supply network pipeline is optimized.

7. A method for optimizing a water supply network according to claim 6, characterized in that: The optimizing of the water supply network pipeline according to the water consumption time period variation coefficient and the pipe section resistance coefficient specifically includes: According to the time period variation coefficient of the water consumption, the peak water consumption period and the low water consumption period of each node in the water supply network pipeline are determined respectively, and the water pump of each node in the water supply network pipeline is determined; When the water consumption is at the peak period, the power of the water pump is adjusted to within the peak range; When the water consumption is at a low peak period, the power of the water pump is adjusted to a low peak range; The valves in each pipeline of the water supply network are adjusted to reduce the resistance of the pipe section.

8. The method for optimizing a water supply network according to claim 1, characterized in that: After optimizing the water supply network pipeline by using the mature hydraulic model, the method includes: Determine the monitoring points in the water supply network according to the pipeline monitoring point information in the water supply network, and monitor the water pressure of the pipelines in the water supply network through the monitoring points; When the water pressure in the pipeline exceeds a preset water pressure threshold, determining whether the pipeline corresponding to the water pressure in the pipeline has burst; If not, respond to the abnormal water pressure event and send the abnormal water pressure information to the water pump administrator for abnormal processing; If so, the valve in the pipeline corresponding to the pipeline water pressure is closed, the pipeline position corresponding to the pipeline water pressure is determined, and the pipeline position is sent to the maintenance department.

9. An optimization device for a water supply network, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform, for example: Collecting pipeline information of the water supply network in the target city through a geographic information system, wherein the pipeline information includes basic pipeline information, pipeline node information, water pump information and geographic information; Determine model parameters according to the pipeline information, construct an initial hydraulic model based on the model parameters, and simplify the initial hydraulic model through a simplification principle algorithm to obtain a simplified hydraulic model; The dynamic pipeline data in the water supply network pipeline is collected in real time through the Internet of Things system, and the water flow operation status of the pipeline in the target city is simulated through the simplified hydraulic model according to the dynamic pipeline data; Comparing the simulated water flow data output by the simplified hydraulic model with the actual water flow data to obtain a simulation error, and adjusting the model parameters based on the simulation error until the simplified hydraulic model converges to obtain a mature hydraulic model; The water supply network pipeline is optimized through the mature hydraulic model.

10. A non-volatile computer storage medium storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Collecting pipeline information of the water supply network in the target city through a geographic information system, wherein the pipeline information includes basic pipeline information, pipeline node information, water pump information and geographic information; Determine model parameters according to the pipeline information, construct an initial hydraulic model based on the model parameters, and simplify the initial hydraulic model through a simplification principle algorithm to obtain a simplified hydraulic model; The dynamic pipeline data in the water supply network pipeline is collected in real time through the Internet of Things system, and the water flow operation status of the pipeline in the target city is simulated through the simplified hydraulic model according to the dynamic pipeline data; Comparing the simulated water flow data output by the simplified hydraulic model with the actual water flow data to obtain a simulation error, and adjusting the model parameters based on the simulation error until the simplified hydraulic model converges to obtain a mature hydraulic model; The water supply network pipeline is optimized through the mature hydraulic model.

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