Method and system for identifying water flow delay time of central heating pipe network

Abstract

The invention provides a method and a system for identifying water flow delay time of a central heating pipe network. According to the method, a digital twin system corresponding to the central heating pipe network is established to obtain water flow delay time from a heat source to each heat exchange station through hydraulic simulation calculation, the water flow delay time is further obtained through a finite impulse response method, and a water flow delay time estimation result with accuracy and robustness is obtained by fusing the two algorithms.

Description

Technical Field

[0001] The present invention relates to the field of centralized heating, in particular to the field of control methods and systems for operation regulation and optimization control of centralized heating systems. Background Art

[0002] Central heating system generally refers to the thermal power plant or heat source plant using boilers or other heating equipment to heat the hot water to the heating standard, and then transport the hot water to the community heat exchange station through the primary network, and then circulate back to the thermal power plant or heat source plant through the return pipe and continue to heat. In the heat exchange station, the hot water heats the water in the secondary pipe network through the heat exchanger, and then the secondary pipe network supplies the hot water to the end users, such as residential buildings. In recent years, with the continuous improvement of people's quality of life, people's requirements for the heating quality and control accuracy of central heating systems have continued to rise. However, the existing central heating system has poor regulation and control effects on heating uniformity and accuracy. One of the reasons is that there is a time delay in the water flow from the heat source through the primary network to each heat exchange station. Different positions, different distances, different pipeline structures or pipe diameters all have an impact on the delay time of the water flow. However, the existing technical heating system is difficult to accurately estimate and predict the delay time of the water flow. This may lead to a decrease in the control accuracy of the system, affect the heating effect, and even cause the automatic control system to fail. Therefore, the prior art urgently needs a method and system that can be widely applicable and stably and reliably estimate the water flow delay time, so as to improve the control accuracy and heating quality of the heating system. Summary of the invention

[0003] In view of the shortcomings and defects of the prior art, the present invention provides a method for identifying the water flow delay time of a centralized heating network, characterized in that the method comprises the following steps:

[0004] S1: Establishing a digital twin system corresponding to the central heating network;

[0005] S2: Using the digital twin system established in step S1, hydraulic simulation is used to calculate and obtain the water flow delay time from the heat source to each heat exchange station.

[0006] Furthermore, the method further comprises the following steps:

[0007] S3: Collect the flow rate and temperature data of each heat exchange station, and use the data to calculate the finite impulse response of the primary water supply temperature of each heat exchange station to the heat source outlet temperature.

[0008] Furthermore, the method further comprises the following steps:

[0009] S4: Taking the water flow delay time obtained in step S2 as the center, construct a normal distribution density function, and apply it to the finite impulse response obtained in step S3, and obtain the water flow delay time result that integrates the digital twin hydraulic simulation and the finite impulse response through a mathematical fusion algorithm.

[0010] Furthermore, the step S1 includes the following sub-steps:

[0011] S11: Collect drawings of the heating pipe network or actually inspect the heating pipe network and obtain the pipe network structure of the heating pipe network;

[0012] S12: Collecting one or more of the positions, types, lengths, diameters, and topological connection relationships of each pipe and / or component in the heating network;

[0013] S13: Using the data acquired in step S11 and step S12, a three-dimensional digital twin system of the heating network is established.

[0014] Furthermore, the step S2 includes the following sub-steps:

[0015] S21a: reading the structure of the pipeline network of the heating pipeline network established in step S1;

[0016] S22a: reading the primary side flow of each heat exchange station in the database, and setting the flow as the flow of each heat exchange station in the hydraulic simulation calculation;

[0017] S23a: solving the flow rate of each pipe section in the pipe network of the entire heating pipe network at this time;

[0018] S24a: further calculating the flow time of each pipeline segment according to the flow rate of each pipeline segment and its length, diameter and other data, and recording it as a matrix weight;

[0019] S25a: The shortest path from the heat source to each heat exchange station is solved by the Dijkstra path search algorithm, thereby obtaining the water flow delay time from the heat source to each heat exchange station.

[0020] Furthermore, the step S2 includes the following sub-steps:

[0021] S21b: reading the structure of the pipeline network of the heating pipeline network established in step S1;

[0022] S22b: Calculate the flow rate of each pipe section in the pipe network of the entire heating pipe network by using a simultaneous circulation adjustment algorithm or Newton's method or Hardy Cross;

[0023] S23b: Further calculate the flow time of each pipeline segment based on data such as the flow rate, length, and diameter of each pipeline segment, and record it as matrix weight;

[0024] S24b: Solve the shortest path from the heat source to each heat exchange station through the Dijkstra path search algorithm, so as to obtain the water flow delay time from the heat source to each heat exchange station.

[0025] Further, the Dijkstra path search algorithm in step S25a or step S24b specifically includes the following steps:

[0026] a. Define each pipeline segment in the heat supply network as a triple (node_a, node_b, weight_(a,b)), where node_a is the starting node of the pipeline, node_b is the ending node of the pipeline, and weight_(a,b) is the flow time of the pipeline segment from node_a to node_b; the node numbers start from 0 and end at N - 1, where N is the total number of nodes;

[0027] b. Initialize the water flow delay time matrix between each node, that is, Dist[N][N] = ∞;

[0028] c. Traverse all pipeline segments. If the delay time from node_a to node_b is less than the value recorded in the current Dist, update the record and update the water flow delay time of all nodes to node_b, that is, if:

[0029] Dist[node_i][node_b] < Dist[node_i][node_a] + Dist[node_a][node_b], then update the record Dist[node_i][node_b] = Dist[node_a][node_b];

[0030] d. Repeat step c until all pipeline segments have been traversed;

[0031] e. Output the water flow delay time from the heat source to the target heat exchange station Where:

[0032] s is the number of the heat source node; v ss is the number of the node of the target heat exchange station ss.

[0033] Further, the specific steps of step S3 are as follows:

[0034] S31: Read the historical primary supply water temperature data of the heat exchange stations to be calculated and the historical supply water temperature data at the heat source outlet from the database, and construct the following matrix:

[0035]

[0036]

[0037] Where y(k) is the primary water supply temperature of the heat exchange station at time k; u(k) is the water supply temperature of the heat source at time k; N is an integer set by the user, indicating the maximum delay time step of the heating system; L is the number of historical data taken;

[0038] S32: Obtain the finite impulse response of the primary water supply temperature of the heat exchange station corresponding to the heat source outlet temperature according to the formula in step S31

[0039]

[0040] S33: The time step index corresponding to the maximum component in is the water flow thermal delay time calculated by the finite impulse response method of the heat exchange station, which is recorded as Where ss is the index of the heat exchange station.

[0041] Furthermore, the specific steps of step S4 are:

[0042] S41: Constructing a normal distribution density function in:

[0043]

[0044]

[0045] is the water flow delay time from the heat source to a certain heat exchange station obtained in step S2;

[0046] S42: Using the normal distribution density function obtained in step S41 as a window function, the window function is applied to the finite impulse response obtained in step S3.

[0047] Furthermore, the water flow delay time results integrating the digital twin hydraulic simulation and the finite impulse response are displayed in a visually significant manner on the schematic diagram of the district heating network.

[0048] The present invention also protects a system for identifying water flow delay time in a central heating network, the system method comprising:

[0049] A model building unit, wherein the model building unit builds a digital twin system corresponding to the central heating network;

[0050] A hydraulic simulation calculation unit, which obtains the water flow delay time from the heat source to each heat exchange station through hydraulic simulation calculation in the digital twin system;

[0051] A finite impulse response calculation unit, which collects flow and temperature data of each heat exchange station and uses the data to calculate a finite impulse response of the primary water supply temperature of each heat exchange station to the heat source outlet temperature;

[0052] The fusion calculation unit constructs a normal distribution density function with the water flow delay time as the center, applies it to the finite impulse response calculation result, and obtains the water flow delay time result that integrates the digital twin hydraulic simulation and the finite impulse response through a mathematical fusion algorithm.

[0053] The present invention can achieve the following technical effects:

[0054] 1. This method can be deployed on a cloud platform, greatly reducing the cost of accurate water flow delay time. It only requires access to sensor data and the establishment of a digital twin model of the pipe network to quickly achieve high-precision and high-stability water flow delay time estimation.

[0055] 2. The present invention simultaneously utilizes digital twin hydraulic simulation and finite impulse response method. Compared with other methods, it integrates two information sources, uses the digital twin hydraulic simulation method to obtain a coarse-step estimate of the thermal delay of the site, and then obtains its precise estimate through finite impulse response. This avoids the problem of inaccurate results obtained when the hydraulic simulation method is used alone, and also avoids the problem of abnormal estimation that may occur when the finite impulse response is used alone, so that the final water flow delay estimate is both robust and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] In order to more clearly illustrate the technical solutions in the specific implementation manner of the present invention, the drawings required for use in the specific implementation manner or the description of the prior art will be briefly introduced below.

[0057] Figure 1 This is a schematic diagram of digital transformation and data collection of an existing site according to an embodiment of the first aspect of the present invention.

[0058] Figure 2 This is a schematic diagram of the water flow delay time calculated by the finite impulse response method for a heat exchange station (Shengyuan Community) in a central heating system.

[0059] Figure 3 Schematic diagram of the normal distribution density function constructed from the water flow delay time obtained through hydraulic calculation.

[0060] Figure 4A schematic diagram of the results obtained after applying the normal distribution density function as a window function to the finite impulse response.

[0061] Figure 5 It is a schematic diagram of the principle that combines hydraulic calculation and finite impulse response algorithm.

[0062] Figure 6 A schematic diagram of the district heating network is provided to display the water flow delay time results in a visually prominent manner. DETAILED DESCRIPTION

[0063] The structure and operation of the present invention will be further described in detail below in conjunction with the accompanying drawings. Obviously, the accompanying drawings are provided only for a better understanding of the present invention and should not be construed as limiting the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] In the description of the present invention, it should be noted that, if the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. appear, the orientation or position relationship indicated is based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, if the terms "first" and "second" appear, they are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0065] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0066] Example 1

[0067] The present embodiment discloses a method for identifying the water flow delay time of a centralized heating network. The so-called water flow delay time refers to the flow time required for hot water starting from the heat source of the centralized heating network to reach a certain heat exchange station from the heat source. The water flow delay time of each heat exchange station is different, and it is also a value that changes with time, and it will change with the change of the network flow distribution on the primary side of the centralized heating network. In order to meet the heating needs of users, it is necessary to adjust the water supply temperature of the heat source of the centralized heating network, and because the thermal delay time of different heat exchange stations is different, the heating and cooling process of the primary side network is dynamic. For example, during the heating process, the thermal power station closer to the heat source has been overheated, while the thermal power station farther away from the heat source is still in an underheated state. Therefore, accurately estimating the water flow delay time of each heat exchange station is of great significance for the precise control of the centralized heating network.

[0068] The method for identifying the water flow delay time of the central heating network disclosed in this embodiment includes the following steps:

[0069] S1: Establishing a digital twin system corresponding to the central heating network;

[0070] S2: Using the digital twin system established in step S1, hydraulic simulation is used to calculate and obtain the water flow delay time from the heat source to each heat exchange station.

[0071] The so-called digital twin system refers to the digital mapping of the central heating network, in which important components include the topological structure of the primary water supply network's pipes, nodes, thermal stations, heat sources, pumps, valves and other components and their mutual adjacency relationships. When establishing a digital twin model, the topological structure of the primary water supply network of the system can be drawn through design data and the topological structure can be calibrated.

[0072] Specifically, the step S1 includes the following sub-steps:

[0073] S11: Collect drawings of the heating pipe network or actually inspect the heating pipe network and obtain the pipe network structure of the heating pipe network;

[0074] S12: Collecting one or more of the positions, types, lengths, diameters, and topological connection relationships of each pipe and / or component in the heating network;

[0075] S13: Using the data acquired in step S11 and step S12, a three-dimensional digital twin system of the heating network is established.

[0076] The process of establishing a digital twin system also includes transforming existing sites, collecting flow and temperature data at the sites, installing flow and temperature sensors at the sites, uploading the data collected by the sensors to the cloud, and processing the data on the cloud server, including cleaning the data uploaded by the sensors, removing outliers, labeling the data, and storing it in a time series database on the cloud.

[0077] The schematic diagram of the digital transformation and data collection of existing sites is as follows: Figure 1 shown.

[0078] After establishing a digital twin system of the centralized heating network, the water flow delay time from the heat source to each heat exchange station can be calculated through mathematical algorithms.

[0079] Specifically, step S2 includes the following sub-steps:

[0080] S21a: reading the structure of the pipeline network of the heating pipeline network established in step S1;

[0081] S22a: reading the primary side flow of each heat exchange station in the database, and setting the flow as the flow of each heat exchange station in the hydraulic simulation calculation;

[0082] S23a: solving the flow rate of each pipe section in the pipe network of the entire heating pipe network at this time;

[0083] S24a: further calculating the flow time of each pipeline segment according to the flow rate of each pipeline segment and its length, diameter and other data, and recording it as a matrix weight;

[0084] S25a: The shortest path from the heat source to each heat exchange station is solved by the Dijkstra path search algorithm, thereby obtaining the water flow delay time from the heat source to each heat exchange station.

[0085] In other alternative embodiments, step S2 includes the following sub-steps:

[0086] S21b: reading the structure of the pipeline network of the heating pipeline network established in step S1;

[0087] S22b: Calculate the flow rate of each pipe section in the pipe network of the entire heating pipe network by using a simultaneous circulation adjustment algorithm or Newton's method or Hardy Cross;

[0088] S23b: further calculating the flow time of each pipeline segment according to the flow rate of each pipeline segment and its length, diameter and other data, and recording it as the matrix weight;

[0089] S24b: Solve the shortest path from the heat source to each heat exchange station through the Dijkstra path search algorithm, so as to obtain the water flow delay time from the heat source to each heat exchange station.

[0090] Specifically, in the step S24a or S23b, the flow rate G of each pipeline p is used to calculate the delay time delay p (s) of each pipeline. The specific formula is:

[0091]

[0092] where the subscript p is the pipeline (pipe) number, p = 1, 2, … M, and l p is the length of pipeline p in meters.

[0093] Among them, the Dijkstra path search algorithm in the step S25a or step S24b specifically includes the following steps:

[0094] a. Define each pipeline segment in the heat supply network as a triple (node_a, node_b, weight_(a,b)), where node_a is the starting node of the pipeline, node_b is the ending node of the pipeline, and weight_(a,b) is the flow time from pipeline segment node_a to node_b; the node numbers start from 0 and end at N - 1, and N is the total number of nodes;

[0095] b. Initialize the water flow delay time matrix between each node, that is, Dist[N][N] = ∞;

[0096] c. Traverse all pipeline segments. If the delay time from node_a to node_b is less than the value recorded in the current Dist, update the record and update the water flow delay time from all nodes to node_b, that is, if:

[0097] Dist[node_i][node_b] < Dist[node_i][node_a] + Dist[node_a][node_b], then update the record Dist[node_i][node_b] = Dist[node_a][node_b];

[0098] d. Repeat step c until all pipeline segments have been traversed;

[0099] e. Output the water flow delay time from the heat source to the target heat exchange station Among them:

[0100] s is the number of the heat source node; v ssIt is the node number of the target heat exchange station ss.

[0101] This method can be deployed on a cloud platform, greatly reducing the cost of accurate water flow delay time. It only requires access to sensor data and the establishment of a digital twin model of the pipeline network to quickly achieve high-precision and high-stability water flow delay time estimation.

[0102] Example 2

[0103] This embodiment is further optimized and improved on the basis of Embodiment 1. The water flow delay time calculated by the digital twin system may be inaccurate, so in this embodiment, the method further includes the following steps:

[0104] S3: Collect the flow rate and temperature data of each heat exchange station, and use the data to calculate the finite impulse response of the primary water supply temperature of each heat exchange station to the heat source outlet temperature.

[0105] S4: Taking the water flow delay time obtained in step S2 as the center, construct a normal distribution density function, and apply it to the finite impulse response obtained in step S3, and obtain the water flow delay time result that integrates the digital twin hydraulic simulation and the finite impulse response through a mathematical fusion algorithm.

[0106] In a specific embodiment, the specific steps of step S3 are:

[0107] S31: The historical primary water supply temperature data of the heat exchange station to be calculated and the historical water supply temperature data of the heat source outlet are read from the database, and the following matrix is ​​constructed:

[0108]

[0109]

[0110] Where y(k) is the primary water supply temperature of the heat exchange station at time k; u(k) is the water supply temperature of the heat source at time k; N is an integer set by the user, indicating the maximum delay time step of the heating system; L is the number of historical data taken;

[0111] S32: Obtain the finite impulse response of the primary water supply temperature of the heat exchange station corresponding to the heat source outlet temperature according to the formula in step S31

[0112]

[0113] S33: The time step index corresponding to the maximum component in is the water flow thermal delay time calculated by the finite impulse response method of the heat exchange station, which is recorded as Where ss is the index of the heat exchange station.

[0114] Figure 2 The figure shows the schematic diagram of the water flow delay time calculated by the finite impulse response method for a heat exchange station (Shengyuan Community) of a central heating system. minute.

[0115] In a specific embodiment, the specific steps of step S4 are:

[0116] S41: Constructing a normal distribution density function in:

[0117]

[0118]

[0119] is the water flow delay time from the heat source to a certain heat exchange station obtained in step S2;

[0120] S42: Using the normal distribution density function obtained in step S41 as a window function, the window function is applied to the finite impulse response obtained in step S3.

[0121] like Figure 3 As shown, it shows a schematic diagram of a normal distribution density function constructed by the water flow delay time obtained by hydraulic calculation. Figure 4 , which shows the result obtained after applying a window function to the finite impulse response.

[0122] This embodiment uses both digital twin hydraulic simulation and finite impulse response methods. Compared with other methods, it integrates two information sources, uses the digital twin hydraulic simulation method to obtain a rough estimate of the thermal delay of the site, and then obtains its precise estimate through finite impulse response, avoiding the problem of inaccurate results when the hydraulic simulation method is used alone, and also avoiding the problem of abnormal estimation that may occur when the finite impulse response is used alone, so that the thermal delay estimate obtained in the end is both robust and accurate. The schematic diagram of its principle is as follows Figure 5 shown.

[0123] In an optimized embodiment, the water flow delay time results integrating the digital twin hydraulic simulation and the finite impulse response can be displayed in a visually significant manner on the schematic diagram of the central heating network, such as Figure 6 shown.

[0124] Example 3

[0125] This embodiment discloses a system for identifying water flow delay time in a central heating network. The system method includes:

[0126] A model building unit, wherein the model building unit builds a digital twin system corresponding to the central heating network;

[0127] A hydraulic simulation calculation unit, which obtains the water flow delay time from the heat source to each heat exchange station through hydraulic simulation calculation in the digital twin system;

[0128] A finite impulse response calculation unit, which collects flow and temperature data of each heat exchange station and uses the data to calculate a finite impulse response of the primary water supply temperature of each heat exchange station to the heat source outlet temperature;

[0129] The fusion calculation unit constructs a normal distribution density function with the water flow delay time as the center, applies it to the finite impulse response calculation result, and obtains the water flow delay time result that integrates the digital twin hydraulic simulation and the finite impulse response through a mathematical fusion algorithm.

[0130] The above embodiments are only used to illustrate the present invention, wherein the structure, connection method and manufacturing process of each component may be changed. Any equivalent transformations and improvements based on this technical solution should not be excluded from the protection scope of the present invention.

Claims

1. A method for identifying water flow delay time in a central heating network. Features: The method comprises the following steps: S1: Establishing a digital twin system corresponding to the central heating network; S2: Using the digital twin system established in step S1, hydraulic simulation is used to calculate and obtain the water flow delay time from the heat source to each heat exchange station.

2. The method according to claim 1, Features: The method further comprises the steps of: S3: Collect the flow rate and temperature data of each heat exchange station, and use the data to calculate the finite impulse response of the primary water supply temperature of each heat exchange station to the heat source outlet temperature.

3. The method according to claim 2, Features: The method further comprises the steps of: S4: Taking the water flow delay time obtained in step S2 as the center, construct a normal distribution density function, and apply it to the finite impulse response obtained in step S3, and obtain the water flow delay time result that integrates the digital twin hydraulic simulation and the finite impulse response through a mathematical fusion algorithm.

4. The method according to claim 1, Features: The step S1 includes the following sub-steps: S11: Collect drawings of the heating pipe network or actually inspect the heating pipe network and obtain the pipe network structure of the heating pipe network; S12: Collecting one or more of the positions, types, lengths, diameters, and topological connection relationships of each pipe and / or component in the heating network; S13: Using the data acquired in step S11 and step S12, a three-dimensional digital twin system of the heating network is established.

5. The method according to claim 1, Features: The step S2 includes the following sub-steps: S21a: reading the structure of the pipeline network of the heating pipeline network established in step S1; S22a: reading the primary side flow of each heat exchange station in the database, and setting the flow as the flow of each heat exchange station in the hydraulic simulation calculation; S23a: solving the flow rate of each pipe section in the pipe network of the entire heating pipe network at this time; S24a: further calculating the flow time of each pipeline segment according to the flow rate of each pipeline segment and its length, diameter and other data, and recording it as a matrix weight; S25a: The shortest path from the heat source to each heat exchange station is solved by the Dijkstra path search algorithm, thereby obtaining the water flow delay time from the heat source to each heat exchange station.

6. The method according to claim 1, Features: The step S2 includes the following sub-steps: S21b: reading the structure of the pipeline network of the heating pipeline network established in step S1; S22b: Calculate the flow rate of each pipe section in the pipe network of the entire heating pipe network by using a simultaneous circulation adjustment algorithm or Newton's method or Hardy Cross; S23b: further calculating the flow time of each pipeline segment according to the flow rate of each pipeline segment and its length, diameter and other data, and recording it as the matrix weight; S24b: The shortest path from the heat source to each heat exchange station is solved by the Dijkstra path search algorithm, thereby obtaining the water flow delay time from the heat source to each heat exchange station.

7. The method according to claim 5 or 6, It is characterized in that: The Dijkstra path search algorithm in step S25a or step S24b specifically includes the following steps: a. Define each pipeline segment in the heat supply pipeline network as a triple (node_a, node_b, weight_(a,b)), where node_a is the starting node of the pipeline, node_b is the ending node of the pipeline, and weight_(a,b) is the flow time of the pipeline segment from node_a to node_b; the node numbers start from 0 and end at N - 1, where N is the total number of nodes; b. Initialize the water flow delay time matrix between each node, that is, Dist[N][N] = ∞; c. Traverse all pipeline segments. If the delay time from node_a to node_b is less than the value recorded in the current Dist, update the record and update the water flow delay time of all nodes to node_b, that is, if: Dist[node_i][node_b]<Dist[node_i][node_a]+Dist[node_a][node_b], then update the record Dist[node_i][node_b] = Dist[node_a][node_b]; d. Repeat step c until all pipeline segments have been traversed; e. Water flow delay time from the output heat source to the target heat exchange station in: s is the number of the heat source node; v ss It is the node number of the target heat exchange station ss.

8. According to the method described in claim 2, It is characterized in that: The specific steps of step S3 are as follows: S31: Read from the database the historical primary supply water temperature data of the heat exchange station to be calculated and the historical supply water temperature data at the heat source outlet, and construct the following matrix: Where y(k) is the primary supply water temperature of the heat exchange station at time k; u(k) is the supply water temperature of the heat source at time k; N is an integer set by the user, representing the maximum delay time steps of the heat supply system; L is the number of historical data taken; S32: Obtain the finite impulse response of the primary water supply temperature of the heat exchange station corresponding to the heat source outlet temperature according to the formula in step S31 S33: The time step index corresponding to the maximum component in is the water flow thermal delay time calculated by the finite impulse response method of the heat exchange station, which is recorded as Where ss is the index of the heat exchange station.

9. According to the method described in claim 3, It is characterized in that: The specific steps of step S4 are as follows: S41: Constructing a normal distribution density function in: is the water flow delay time from the heat source to a certain heat exchange station obtained in step S2; S42: Use the normal distribution density function obtained in step S41 as the window function and apply this window function to the finite impulse response obtained in step S3.

10. According to the method described in claim 3, It is characterized in that: The water flow delay time result that integrates digital twin hydraulic simulation and finite impulse response is displayed in a visually prominent manner on the schematic diagram of the central heating pipeline network.

11. A system for identifying the water flow delay time of a central heating pipeline network, It is characterized in that: The system method includes: A model establishment unit that establishes a digital twin system corresponding to the central heating pipeline network; A hydraulic simulation calculation unit that obtains the water flow delay time from the heat source to each heat exchange station through hydraulic simulation calculation in the digital twin system; A finite impulse response calculation unit that collects the flow rate and temperature data of each heat exchange station and calculates the finite impulse response of the primary supply water temperature of each heat exchange station to the heat source outlet temperature using the data. The fusion calculation unit constructs a normal distribution density function with the water flow delay time as the center, applies it to the finite impulse response calculation result, and obtains the water flow delay time result that integrates the digital twin hydraulic simulation and the finite impulse response through a mathematical fusion algorithm.

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