Method for calculating flow rate of heat exchanger of circulating water system based on digital twin model

Abstract

The application provides a method for calculating the flow rate of a heat exchanger in a circulating water system based on a digital twin model, comprising: obtaining a circulating water system flow description file and parsing it to determine the topology of the circulating water system and the physical parameters of the key equipment; based on the topology and the physical parameters of the key equipment in the circulating water system, a digital twin model framework for the circulating water system is constructed; the description of fluid flow and heat exchange in each heat exchanger is established and loaded onto the digital twin model framework to form a digital twin model representing the fluid flow characteristics and heat exchange characteristics; based on the digital twin model, fluid flow and heat exchange simulation is performed to estimate the fluid flow rate inside each heat exchanger in the circulating water system to generate the flow rate detection results of each heat exchanger. This method relies on the system topology and the twin model to synchronously obtain the heat exchanger flow rate and perform correlation analysis, improve the determination rationality, and support the optimization of the circulating water system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital twinning, in particular to a method for calculating flow velocity of a heat exchanger of a circulating water system based on a digital twinning model. BACKGROUND

[0002] In the field of industrial production, the circulating water system is a core auxiliary system for ensuring the continuous operation of process equipment in the oil refining, chemical and other industries. As a key device for heat exchange between hot and cold media, the rationality of the internal fluid flow velocity of the heat exchanger is directly related to the system operation efficiency, equipment life and production economy. If the flow velocity in the heat exchanger is too low, suspended solids, silt and other impurities in the water will deposit on the surface of the heat exchange tube to form a scale layer, which will reduce the heat transfer coefficient and affect the heat exchange effect, and will also cause under-deposit corrosion to accelerate tube wall perforation. If the flow velocity is too high, it will increase the pressure drop of the pipeline, leading to an increase in pump power consumption, and will also increase the frequency of equipment maintenance. According to the national standard (such as GB / T50050-2017), the flow velocity in the tube of the heat exchanger should not be less than 1.0 m / s, and the flow velocity in the shell should not be less than 0.3 m / s. Reasonable flow velocity can also inhibit the growth of microorganisms in water, avoid excessive turbidity and total iron content, and reduce unplanned downtime losses. Therefore, there is an urgent industrial need for accurate control and system-level optimization of the flow velocity of the heat exchanger.

[0003] Currently, for the control and optimization of the flow velocity of the heat exchanger of the circulating water system, the existing technology usually uses single-point detection instruments (such as ultrasonic flow meters and portable flow meters) to measure the flow velocity at a specified position of a single heat exchanger. Then, the flow velocity calculation and rationality determination of a single device are carried out in combination with the isolated physical parameters (such as the inner diameter of the tube and the number of tube passes) of the heat exchanger. Finally, local adjustment measures (such as pipeline throttling or expansion of a single device) are separately developed based on the flow velocity detection results of a single heat exchanger.

[0004] However, the existing scheme can only realize isolated detection and calculation of the flow velocity of a single heat exchanger, and cannot establish a flow velocity correlation between multiple heat exchangers. It is difficult to verify the accuracy of the flow velocity detection results of a single device from the system level, and it is also impossible to analyze the influence of the flow velocity change of a heat exchanger on other related heat exchangers. SUMMARY

[0005] To solve the above technical problems, the present application provides a method for calculating the flow velocity of a heat exchanger of a circulating water system based on a digital twinning model, at least to alleviate the above technical problems.

[0006] The technical scheme provided by the embodiments of the present application is as follows:

[0007] A method for calculating the flow velocity of a heat exchanger of a circulating water system based on a digital twinning model, comprising:

[0008] Step 1, obtain a circulating water system flow description file and parse it to determine the topology of the circulating water system and the physical parameters of the key equipment in the circulating water system, the key equipment at least including a heat exchanger, a circulating water pump, and a cooling tower;

[0009] Step 2, based on the topology of the circulating water system and the physical parameters of the key equipment in the circulating water system, a digital twin model framework for the circulating water system is constructed;

[0010] Step 3, the description of fluid flow and heat exchange in each heat exchanger is established and loaded into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat exchange characteristics;

[0011] Step 4, based on the digital twin model representing fluid flow characteristics and heat exchange characteristics, fluid flow and heat exchange simulation is performed to estimate the fluid flow rate inside each heat exchanger in the circulating water system to generate flow rate detection results for each heat exchanger, and to estimate the mutual influence degree of flow rate between heat exchangers to generate flow rate correlation analysis results between heat exchangers.

[0012] The scheme of the present application has the following technical benefits:

[0013] Firstly, for the bottleneck of the traditional scheme "without system level device connection relationship support, only isolated analysis of single heat exchanger", step 1 determines the key equipment physical parameters and system topology including heat exchanger, circulating water pump and cooling tower by obtaining and parsing the circulating water system flow description file, which can clearly reflect the pipe network connection relationship of multiple heat exchangers in the circulating water system (such as parallel / series pipeline layout, and flow distribution path with circulating water pump), and lay a foundation for subsequent establishment of flow rate correlation of multiple heat exchangers, which is different from the traditional analysis method relying only on isolated parameters of single device, so that the flow rate calculation is upgraded from "single point view" to "system view".

[0014] Secondly, for the limitation of the traditional scheme "depending on single point detection instrument, only measuring flow rate at single specified position", step 2 constructs a digital twin model framework for the circulating water system based on the topology and physical parameters of the key equipment, and step 3 further loads the description of fluid flow and heat exchange in each heat exchanger to form a complete digital twin model representing fluid flow characteristics and heat exchange characteristics, which can simulate the dynamic fluid flow process of the entire circulating water system (such as circulating water pump flow distribution, and influence of pipeline resistance on flow rate), instead of the traditional static data detection of single local position; the estimated internal flow rate of single heat exchanger through model simulation can be combined with the overall flow law of the system, which is more systematic and reasonable than the traditional single point detection, and reduces the flow rate determination error caused by local detection deviation.

[0015] Finally, to solve the core problem of the traditional scheme that "it is unable to analyze the flow rate correlation of multiple heat exchangers and difficult to verify the accuracy of single detection and the mutual influence of prediction", step 4 synchronously generates "flow rate detection results of each heat exchanger" and "flow rate correlation analysis results between heat exchangers" based on the digital twin model representing the fluid flow characteristics and heat exchange characteristics. On the one hand, the rationality of the single flow rate detection result can be verified through the flow rate correlation analysis result between heat exchangers (for example, when the flow rate of a certain heat exchanger is abnormal, it can be judged through correlation analysis whether it is a problem of the equipment itself or affected by other heat exchangers, avoiding the traditional misjudgment); on the other hand, the influence degree of the flow rate change of a certain heat exchanger on other related heat exchangers can be determined (for example, when the flow rate of a certain heat exchanger is increased due to pipeline adjustment, it can be predicted through correlation analysis whether it will cause the flow rate of the parallel heat exchanger to decrease), solving the technical gap that the traditional scheme cannot control the flow rate from the system level, and providing more comprehensive decision basis for the overall optimization of the subsequent circulating water system. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 FIG. 1 is a flowchart of a method for calculating the flow rate of a heat exchanger of a circulating water system based on a digital twin model according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] As shown in FIG. 1, the present application provides a method for calculating the flow rate of a heat exchanger of a circulating water system based on a digital twin model, which comprises: Figure 1 Step 1, obtaining a circulating water system flow description file and parsing it to determine the topological structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, wherein the key equipment at least includes a heat exchanger, a circulating water pump and a cooling tower;

[0018] Step 2, based on the topological structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, constructing a digital twin model framework for the circulating water system;

[0019] Step 3, establishing the description of fluid flow and heat exchange in each heat exchanger and loading it into the digital twin model framework of the circulating water system to form a digital twin model representing the fluid flow characteristics and heat exchange characteristics;

[0020] Step 4, based on the digital twin model representing the fluid flow characteristics and heat exchange characteristics, simulating the fluid flow and heat exchange, estimating the fluid flow rate inside each heat exchanger in the circulating water system to generate the flow rate detection results of each heat exchanger, and at the same time estimating the mutual influence degree of the flow rate between each heat exchanger to generate the flow rate correlation analysis results between heat exchangers.

[0021]

[0022] ​Optionally, in step 1, the circulation water system flow description file is acquired and parsed to determine the topology of the circulation water system and the physical parameters of the key equipment in the circulation water system, the key equipment at least including a heat exchanger, a circulation water pump and a cooling tower, specifically: the circulation water system flow description file is acquired and parsed according to the equipment range of the physical parameters to extract the physical parameters of the key equipment, the pipe network arrangement information, the key equipment connection relationship information and the medium flow path information to generate the topology of the circulation water system, and the physical parameters of the key equipment are marked on the topology.

[0023] Optionally, the circulation water system flow description file is acquired and parsed according to the equipment range of the physical parameters to extract the physical parameters of the key equipment, the pipe network arrangement information, the key equipment connection relationship information and the medium flow path information to generate the topology of the circulation water system, and the physical parameters of the key equipment are marked on the topology, specifically including:

[0024] In step 11, the circulation water system flow description file is acquired and parsed according to the equipment range of the physical parameters to extract the physical parameters of the key equipment, the pipe network arrangement information, the key equipment connection relationship information and the medium flow path information.

[0025] In step 12, the static topology feature and the dynamic association description feature are generated according to the pipe network arrangement information, the key equipment connection relationship information and the medium flow path information.

[0026] In step 13, the circulation water system topology association matrix is constructed according to the static topology feature and the dynamic association description feature, the row of the matrix represents the topology node identification number, the column represents the identification number of the key equipment, and the element at the intersection of the row and the column is the association state value.

[0027] In step 14, the topology of the circulation water system is generated according to the circulation water system topology association matrix, and the physical parameters of the key equipment are marked on the topology.

[0028] Preferably, the specific implementation process of step 11 is as follows: first, determine the range of equipment for extracting physical parameters (at least including heat exchangers, circulating water pumps, cooling towers), and obtain the circulating water system process description file (the file needs to cover the pipe network layout diagram, equipment parameter table, medium flow direction description and other core contents) with the equipment range as the screening basis; then, the circulating water system process description file is parsed, the physical parameters of the key equipment (such as the number of tubes / tube passes / inner diameter of tubes of the heat exchanger, the head curve / rated flow of the circulating water pump, the processing capacity / fan power of the cooling tower) are extracted from the file, the pipe network arrangement information (the direction of the water supply pipeline / return water pipeline, the distribution position of the branch pipeline), the connection relationship information of the key equipment (the interface number of the heat exchanger and the pipeline, the access node of the circulating water pump and the pipe network, the connection port of the cooling tower and the return water pipeline), and the medium flow path information (the complete path node sequence of the circulating water from the pump outlet to the heat exchanger inlet, and then to the cooling tower inlet) are extracted; finally, all the extracted information is arranged in the format of “parameter type-data content-source label” to generate the initial parameter set of the circulating water system. This technology is different from the traditional indiscriminate extraction of file information. By presetting the equipment range for directional parsing, the information redundancy caused by extracting irrelevant equipment parameters can be avoided, and higher targeted basic data for subsequent generation of the topological structure is provided. For example, when extracting the physical parameters of the heat exchanger, the general range is set to 100-1000 tubes and 15-50mm inner diameter of tubes. In actual application, a refinery heat exchanger has 300 tubes and 32mm inner diameter of tubes.

[0029] Preferably, in the specific technical implementation of step 12: taking the initial parameter set of the circulating water system as the processing object, the pipe network arrangement information, the connection relationship information of the key equipment and the medium flow path information are separated; the pipe network arrangement information and the connection relationship information of the key equipment are subjected to static feature extraction, and the information that does not change with the running state, such as the direction of the pipeline, the spatial position coordinates of the equipment, and the fixed interface connection relationship, is arranged into a static topological feature document (each entry in the document corresponds to the associated data of “pipeline number-direction description-connection equipment number-spatial coordinates”); the medium flow path information is subjected to dynamic feature extraction, and the influence law of the equipment start-stop state (such as single / double opening of the circulating water pump, number of operating cooling towers) on the medium flow direction, the flow distribution proportion logic of the branch pipeline (such as proportional distribution according to the pipe diameter, distribution according to the heat exchange load demand) and other information that changes with the running state are analyzed, and arranged into a dynamic associated description feature document (each entry in the document corresponds to the associated data of “running condition-medium flow direction adjustment rule-flow distribution logic”); the static topological feature document and the dynamic associated description feature document are used as the basic input for subsequent construction of the topological association matrix. This technology is different from the traditional method of only extracting static pipe network information. By separating static and dynamic features, the dual attributes of “fixed structure” and “dynamic operation” of the system can be fully reflected, and support for subsequent generation of the topological structure that fits the actual operation is provided.

[0030] Preferably, the specific implementation process of step 13 is as follows: taking the static topology feature document and the dynamic association description feature document as the processing object, first extract all pipeline two-end connection points from the static topology feature document, define each connection point as a topology node, assign a unique identification number to each topology node (the numbering rule is "region code-node type code-sequence number", such as "GT-H-001" representing water supply network heat exchanger interface node 001), and record the corresponding key equipment type of each topology node (such as heat exchanger interface node, water pump outlet node, cooling tower inlet node); based on the topology node identification number and the key equipment identification number (extracted from the circulating water system initial parameter set), a circulating water system topology association matrix is constructed, the row of the circulating water system topology association matrix represents the topology node identification number (N rows in total, N is the total number of topology nodes), the column represents the key equipment identification number (M columns in total, M is the total number of key equipment), and the element at the intersection of the matrix row and column is the association state value (when the value is 1, it means that the topology node is directly connected with the corresponding key equipment, and when the value is 0, it means that the topology node is not directly connected with the corresponding key equipment); then, the topology association matrix is processed to remove redundant information, and the repeated association state records in the matrix are deleted (such as repeated connection marks of the same equipment and the same pipeline two-end node, and multiple marks of the same node and the same equipment), to obtain an optimized circulating water system topology association matrix. This technology is different from the traditional way of describing the association of equipment and nodes with words, and realizes the quantitative expression of the association relationship through matrix presentation, which can more clearly reflect the corresponding relationship between nodes and equipment and reduce the complexity of subsequent combing of pipe network path. For example, a certain petrochemical circulating water system contains 200 topology nodes (N=200) and 50 key equipment (M=50), and the constructed topology association matrix is 200 rows x 50 columns, and the element at the intersection of (GT-H-001, E-132) in the matrix is 1, representing that the topology node GT-H-001 is directly connected with the heat exchanger E-132.

[0031] Preferably, in a scenario, step 14 is specifically implemented: taking the optimized circulating water system topology association matrix as the core processing object, combining the pipeline route information in the static topology feature document, and combing the complete pipe network path formed by connecting various key devices through the topology node (the combing logic is: starting from the topology node corresponding to the circulating water pump outlet, connecting to the heat exchanger interface topology node according to the association relationship in the matrix, and then connecting to the cooling tower inlet topology node to form a closed pipe network path); on the basis of the combing pipe network path, the circulating water system topology structure is generated (the structure is presented in the form of a graphical or node-pipeline association table, including the complete link of "topology node number-connection pipeline number-association device number"); finally, the physical parameters of each key device are extracted from the initial parameter set of the circulating water system, and are labeled at the corresponding device location in the circulating water system topology structure in the format of "device number-physical parameter name-parameter value", to generate the circulating water system topology structure labeled with the physical parameters of the key devices. This technology is different from the traditional topology structure that only presents the connection relationship of the pipe network. By labeling the physical parameters of the key devices, the topology structure can simultaneously carry dual information of "structure association" and "parameter attribute", directly providing integrated basic data for subsequent construction of the digital twin model framework of the circulating water system, avoiding the secondary matching work of parameters and structure. For example, at the location of the heat exchanger E-132 in the topology structure, the physical parameters "number of pipes: 300, number of pipe passes: 2, tube diameter: 32mm" are labeled.

[0032] Optionally, step 2, based on the topology structure of the circulating water system and the physical parameters of the key devices in the circulating water system, constructs a digital twin model framework for the circulating water system, specifically: according to the topology structure of the circulating water system and the physical parameters of the key devices in the circulating water system, a key device physical parameter-topology node mapping table is established to construct a digital twin model framework for the circulating water system.

[0033] Optionally, according to the topology structure of the circulating water system and the physical parameters of the key devices in the circulating water system, a key device physical parameter-topology node mapping table is established to construct a digital twin model framework for the circulating water system, specifically including:

[0034] Step 21, according to the topology structure of the circulating water system and the physical parameters of the key devices in the circulating water system, a key device physical parameter-topology node mapping table is established;

[0035] Step 22, based on the key device physical parameter-topology node mapping table, the pipe network topology form is restored and the physical parameters of each key device are associated to the corresponding topology node to generate a circulating water system topology framework;

[0036] Step 23, build a dedicated model module for different types of key equipment, and integrate it into the circulating water system topology framework to form the digital twin model framework of the circulating water system.

[0037] Preferably, the specific implementation process of step 21 is as follows: taking the "circulating water system topology structure labeled with key equipment physical parameters" generated in step 14 as the processing object, extracting the unique identification number of each key equipment (such as heat exchanger E-101, circulating water pump P-201, cooling tower CT-301), the corresponding complete set of physical parameters (number of tubes / passage number / inner diameter of tube of heat exchanger, head curve / rated speed of circulating water pump, processing capacity / fan power of cooling tower), and all topological node identification numbers connected by the key equipment in the topology structure (such as heat exchanger E-101 connecting nodes N-005 and N-006); the extracted "key equipment identification number-physical parameter-topological node identification number" is associated one by one, sorted according to the field format of "equipment type-equipment identification number-topological node identification number-physical parameter name-physical parameter value", and a key equipment physical parameter-topological node mapping table is generated. This technology is different from the traditional way of storing device parameters and topological nodes separately. By establishing an integrated mapping table, the quick association of parameters and topological positions can be realized directly, avoiding the secondary matching of parameters and nodes in subsequent model building, and improving the framework construction efficiency. For example, for heat exchanger E-101, the mapping table records "heat exchanger-E-101-N-005 / N-006-tube inner diameter-32mm" "heat exchanger-E-101-N-005 / N-006-passage number-2" and other items, and circulating water pump P-201 records "water pump-P-201-N-010-rated flow-600m 3 / h" and other items, where the tube inner diameter has a general value range of 15-50mm, and the rated flow has a general value range of 200-2000m 3 / h, and the specific value is determined according to system requirements.

[0038] Preferably, in the specific technical implementation of step 22: taking the key equipment physical parameter-topological node mapping table as the processing object, first extract all topological node identification numbers and corresponding node connection relationships (obtain the pipeline connection information between nodes from the topological structure of step 14) in the mapping table, restore the pipe network topological form according to the logic of "topological node identification number-adjacent node identification number-connection pipeline specification" (for example, node N-005 is connected to node N-006 through DN200 pipeline, and node N-006 is connected to node N-007 through DN150 pipeline), form a visual or structured pipe network topological sketch; then extract the physical parameters of each key equipment from the key equipment physical parameter-topological node mapping table, and associate it to the corresponding topological node (for example, annotate the pipe length and column tube inner diameter of heat exchanger E-101 beside node N-005 / N-006, and annotate the rated flow and head curve of circulating water pump P-201 beside node N-010); finally, perform integrity check on the associated pipe network topological sketch (check whether there are nodes with unassociated parameters, and whether there are devices with missing parameters), and generate a circulating water system topological framework after passing the check. This technology is different from the traditional topological framework which only presents the connection form of the pipe network. By directly associating the equipment physical parameters beside the topological nodes, the framework can carry both structure and parameter information, providing direct data support for the integration of subsequent equipment-specific modules. For example, when restoring the pipe network of a certain petrochemical system, the node N-005 is annotated with "associated equipment E-101: column tube inner diameter 32mm, pipe length 2", and the connection pipeline specification is generally DN50-DN300, and the specific DN200 is taken for a certain section of pipeline.

[0039] Preferably, in one scenario, step 23 is implemented as follows: based on the topology framework of the circulating water system, different types of key equipment are built with dedicated model modules. For heat exchangers, a "heat exchanger flow-heat transfer calculation module" is built, which has built-in fluid flow resistance calculation logic (based on pipe inside diameter and pipe length to calculate pressure loss) and heat transfer characteristic calculation logic (based on pipe number and heat transfer area to calculate heat transfer amount). The module inputs are flow data and temperature data from the topology nodes, and the outputs are flow rate and temperature rise data. For circulating water pumps, a "pump operating characteristic module" is built, which has built-in head-flow curve matching logic (based on rated speed to correct actual head) and power calculation logic (based on actual flow and efficiency curve to calculate energy consumption). The module input is the pressure demand of the pipe network, and the output is the actual flow and operating power. For cooling towers, a "cooling tower cooling efficiency module" is built, which has built-in air volume-cooling temperature difference calculation logic (based on fan power to adjust air volume) and water quality parameter control logic (based on treatment capacity to adjust water replenishment rate). The module inputs are inlet water temperature and flow, and the outputs are outlet water temperature and turbidity control value. After the modules are built, they are connected to the topology nodes of the corresponding equipment in the circulating water system topology framework through a pre-set "module-topology node interface" (e.g., "heat exchanger flow-heat transfer calculation module" connects to nodes N-005 / N-006, and "pump operating characteristic module" connects to node N-010). This ensures that the modules can obtain input data from the topology nodes and output calculation results to the topology nodes, and the integrated digital twin model framework of the circulating water system is formed. This technology is different from the traditional method of using general model modules to adapt to all equipment. By building dedicated modules for different equipment, the core operating characteristics of the equipment can be more accurately matched, and the reliability of subsequent simulation calculations can be improved. For example, in the "heat exchanger flow-heat transfer calculation module", the pressure loss calculation logic adjusts the calculation coefficient according to the 32mm tube inside diameter in the mapping table, and the "pump operating characteristic module" matches the corresponding head curve according to the rated flow of 600m 3 / h. The fan power is generally in the range of 15-100kW, and the specific value for a certain cooling tower is 37kW.

[0040] Optionally, step 3, the description of fluid flow and heat transfer in each heat exchanger is established and loaded into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat transfer characteristics. Specifically:

[0041] According to the description rules of fluid mass conservation, fluid motion resistance, and heat transfer, the description of fluid flow and heat transfer in each heat exchanger is established and loaded into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat transfer characteristics.

[0042] Optionally, the description of fluid flow and heat exchange in each heat exchanger is established according to the description rules representing fluid mass conservation, the description rules representing fluid motion resistance, and the description rules representing heat transfer, and is loaded onto the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat exchange characteristics, specifically including:

[0043] Step 31, obtain the description rules representing fluid mass conservation, the description rules representing fluid motion resistance, and the description rules representing heat transfer, and define the physical meaning and value range of the variables in each rule to generate a fluid flow-heat exchange basic description rule and a variable definition table;

[0044] Step 32, according to the fluid flow-heat exchange basic description rule and the variable definition table, calculate the resistance characteristics of the pipeline, the heat exchange characteristics corresponding to the corrected heat transfer area, and the fluid distribution flow of each tube pass to establish the description of fluid flow and heat exchange in each heat exchanger;

[0045] Step 33, access the heat exchanger characteristic loading interface in the digital twin model framework of the circulating water system to load the description of fluid flow and heat exchange in each heat exchanger.

[0046] Preferably, the specific implementation process of step 31 is as follows: first, determine the core operating characteristic requirements of the heat exchanger in the circulating water system, obtain the description rules representing the fluid mass conservation (clearly the relationship between medium density, flow velocity and flow area, that is, under the same flow, the smaller the flow area, the greater the flow velocity, and the circular cross-section characteristics of the heat exchanger tube need to be matched), the description rules representing the fluid motion resistance (clearly the relationship between flow velocity, pressure loss and pipe friction characteristics, that is, the greater the flow velocity or the higher the roughness of the inner wall of the tube, the greater the pressure loss, and the series resistance superposition logic of the number of heat exchanger tube needs to be combined), and the description rules representing heat transfer (clearly the relationship between temperature change, heat transfer and heat transfer characteristics, that is, the greater the heat transfer area or the greater the temperature difference between the cold and hot sides of the medium, the greater the heat transfer, and the heat transfer of the heat exchanger shell side baffle needs to be adapted to the strengthening effect); then define the physical meaning and value range of the variables in each rule, such as the description rule representing the fluid mass conservation, the single tube cross-sectional area corresponding to the heat exchanger tube diameter calculation (the general value range is calculated based on the tube diameter of 15-50mm, and the cross-sectional area corresponding to 32mm is taken for a specific heat exchanger), the flow velocity is set to 0.8-2.0m / s according to the circulating water medium, and the heat transfer area is calculated according to the number of heat exchanger tubes and single tube length (the general range of tube length is 2-8m, and 4m is taken specifically); finally, the three description rules and corresponding variable definitions are arranged according to the field format of "rule type-variable name-physical meaning-value range-adaptation of heat exchanger components", to generate the fluid flow-heat transfer basic description rule and variable definition table, which serves as the core basis for subsequent adaptation with specific heat exchanger parameters. This technology is different from the traditional way of only defining general physical rules, by incorporating the column tube, tube, baffle and other exclusive structural characteristics of the heat exchanger into the rules, making the rules have higher equipment adaptability, avoiding the disconnection between subsequent calculation and actual equipment characteristics.

[0047] Preferably, in the specific technical implementation of step 32: taking the fluid flow-heat exchange based description rules and variable definition table, and the "circulating water system topology annotated with key equipment physical parameters" generated in step 14 as the processing object, the physical parameters of a certain heat exchanger (such as the tube inside diameter of 32 mm, the tube length of 4 m, the tube number of 2, the baffle number of 10, and the baffle spacing of 200 mm) are first extracted from the topology structure; based on the description rules representing fluid motion resistance and the extracted parameters, the pipeline resistance characteristics along the way are calculated (combining the tube length of 4 m, the tube inside diameter of 32 mm, and the inner wall roughness, according to the logic of "resistance is positively correlated with tube length and negatively correlated with tube diameter" in the rules, the unit length resistance value of the tube passage of the heat exchanger is obtained); based on the description rules representing heat transfer and the baffle parameters, the heat transfer characteristics corresponding to the heat transfer area are corrected (because the baffle can enhance the shell side medium turbulence, according to the logic of "the smaller the baffle spacing, the higher the heat transfer enhancement coefficient" in the rules, the baffle spacing of 200 mm corresponds to a heat transfer enhancement coefficient of 1.1, which is used to correct the basic heat transfer area calculated according to the tube area); based on the description rules representing fluid mass conservation and the tube number of 2, the fluid distribution flow of each tube passage is split (according to the logic of "multiple tube passages are evenly distributed" in the rules, the total circulating water flow of the heat exchanger is evenly distributed to the two tube passages, and the single tube passage flow is obtained); the above parameter extraction and calculation operations are repeated for each heat exchanger, and the pipeline resistance characteristics along the way, the corrected heat transfer characteristics, and the tube passage flow distribution results of each heat exchanger are arranged in the format of "heat exchanger identification number-resistance characteristic value-corrected heat transfer coefficient-single tube passage flow" to generate a single heat exchanger fluid flow-heat exchange description document, and the description documents of all heat exchangers together constitute a circulating water system heat exchanger flow-heat exchange description collection. This technology is different from the traditional method of calculating the characteristics of heat exchangers using general formulas. By adapting the rules to the actual physical parameters (such as the specific inside diameter and the tube number) of each heat exchanger one by one, the calculation results are more consistent with the actual operating state of the equipment, and the reliability of the description is improved.

[0048] Preferably, in a scenario, step 33 is specifically implemented as follows: taking the heat exchanger flow-heat exchange description set of the circulating water system and the "digital twin model framework of the circulating water system" generated in step 23 as the processing object, first determine the "heat exchanger characteristic loading interface" (which is used to receive the heat exchanger flow-heat exchange description document and realize the association of the description data and the framework topology node, and the interface needs to support accurate matching according to the heat exchanger identification number) preset in the digital twin model framework of the circulating water system; select the description document of a single heat exchanger from the circulating water system heat exchanger flow-heat exchange description set, import it into the digital twin model framework of the circulating water system through the "heat exchanger characteristic loading interface", and at the same time select the corresponding topology node (such as the heat exchanger E-101 corresponding nodes N-005 and N-006) of the heat exchanger in the framework topology structure in the interface, so that the resistance characteristics, heat exchange characteristics and other data in the description document are associated with the topology node, and ensure that the node can call the corresponding characteristic data in subsequent simulation; repeat the import operation to load the flow-heat exchange description documents of all heat exchangers into the framework one by one and associate the corresponding topology nodes; after loading, perform loading verification for each heat exchanger, input the simulation flow (such as inputting the total flow 100 m 3 / h to the node N-005 of E-101) to the associated topology node through the framework, call the loaded flow-heat exchange description data to calculate the flow rate and heat exchange amount, and if the calculation result (such as flow rate 1.1 m / s, heat exchange amount 450 kW) is within the value range of the fluid flow-heat exchange basic description rule and variable definition table, it is determined that the loading is successful; after all the heat exchangers pass the loading verification, the framework automatically integrates to form a digital twin model representing the fluid flow characteristics and heat exchange characteristics. This technology is different from the traditional way of directly storing characteristic data in the framework, and realizes the accurate association of description data and topology node through a dedicated interface, avoids the disconnection of data and equipment topology position after loading, ensures that the characteristic data can be called cooperatively with the pipe network flow logic in subsequent simulation, and improves the overall consistency of the model. For example, after loading the description document of heat exchanger E-101, input the total flow 100 m 3 / h, based on the allocation logic of "2 tube passes" in the description document, calculate the single tube pass flow 50 m 3 / h, combined with the flow cross-sectional area of 32 mm inner diameter, get the flow rate 1.1 m / s, which is within the value range of 0.8-2.0 m / s, and pass the verification.

[0049] Optionally, step 4, based on the digital twin model representing fluid flow characteristics and heat exchange characteristics, fluid flow and heat exchange simulation is performed to estimate the fluid flow rate inside each heat exchanger in the circulating water system to generate the flow rate detection results of each heat exchanger, and to estimate the mutual influence degree of flow rate between heat exchangers to generate the flow rate correlation analysis results between heat exchangers, specifically: based on the target operation data of each key equipment in the circulating water system, based on the digital twin model representing fluid flow characteristics and heat exchange characteristics, fluid flow and heat exchange simulation is performed to generate the flow rate detection results of each heat exchanger, and based on the determined influence dimension of the flow rate correlation between heat exchangers, the mutual influence degree of flow rate between heat exchangers is estimated to generate the flow rate correlation analysis results between heat exchangers.

[0050] Optionally, based on the target operation data of each key equipment in the circulating water system, based on the digital twin model representing fluid flow characteristics and heat exchange characteristics, fluid flow and heat exchange simulation is performed to generate the flow rate detection results of each heat exchanger, and based on the determined influence dimension of the flow rate correlation between heat exchangers, the mutual influence degree of flow rate between heat exchangers is estimated to generate the flow rate correlation analysis results between heat exchangers, specifically including:

[0051] Step 41, determine the target operation data of each key equipment in the circulating water system, including fluid flow related target data and heat exchange related target data, to call the fluid flow characteristic description and heat exchange characteristic description of each heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, calculate the initial flow rate estimation value and correct it to obtain the flow rate estimation value and generate the flow rate detection results of each heat exchanger accordingly;

[0052] Step 42, based on the determined influence dimension of the flow rate correlation between heat exchangers, perform pairwise correlation simulation in the digital twin model representing fluid flow characteristics and heat exchange characteristics to generate a flow rate correlation influence matrix between heat exchangers as the flow rate correlation analysis results between heat exchangers.

[0053] Optionally, step 41, determine the target operation data of each key equipment in the circulating water system, including fluid flow related target data and heat exchange related target data, to call the fluid flow characteristic description and heat exchange characteristic description of each heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, calculate the initial flow rate estimation value and correct it to obtain the flow rate estimation value and generate the flow rate detection results of each heat exchanger accordingly, specifically including:

[0054] Step 411, determine the target operation data of each key equipment in the circulating water system, including fluid flow related target data and heat exchange related target data;

[0055] Step 412, call the fluid flow characteristic and heat exchange characteristic description of each heat exchanger in the digital twin model representing the fluid flow characteristic and heat exchange characteristic, calculate the initial circulating water flow rate of each heat exchanger based on the fluid flow related target data through flow distribution calculation; based on the initial circulating water flow rate of each heat exchanger, combined with the flow area of the heat exchanger, obtain the initial flow velocity estimation value;

[0056] Step 413, based on the pipeline position of the heat exchanger in the circulating water system, correct the initial flow velocity estimation value to obtain the flow velocity estimation value;

[0057] Step 414, call the heat exchange characteristic description of each heat exchanger in the digital twin model representing the fluid flow characteristic and heat exchange characteristic, calculate the theoretical heat exchange characteristic value according to the cold and hot side target temperature of the heat exchanger and the process side heat load, determine the matching degree of the effective flow velocity estimation value and the corresponding heat exchange related target data, to generate the flow velocity detection result of each heat exchanger.

[0058] Preferably, the specific implementation process of step 411 is as follows: taking the digital twin model framework (generated in step 23) of the circulating water system as a reference, determine the key equipment target operation data range to be collected, wherein the fluid flow related target data includes circulating water pump outlet target flow, circulating water pump outlet target pressure, cooling tower backwater target flow, pipe network main pipe target flow velocity, and the heat exchange related target data includes each heat exchanger cold and hot side target inlet temperature, each heat exchanger cold and hot side target outlet temperature, each heat exchanger process side target heat load, and cooling tower outlet target water temperature; extract the above data through the historical operation database of the circulating water system, design specification file or process requirement document, and arrange them in the format of "equipment type-equipment identification number-data type-target value" to generate the key equipment target operation data set. This technology is different from the traditional method of collecting only single flow data or heat exchange data. By integrating fluid-heat exchange two-dimensional target data, it provides complete input basis for subsequent flow velocity estimation and heat exchange matching, and avoids estimation deviation caused by data loss. For example, the circulating water pump outlet target flow is generally 300-1500 m 3 / h, and the circulating water pump of a certain oil refinery is 800 m 3 / h; the heat exchanger cold and hot side target temperature difference is generally 5-20℃, and a certain heat exchanger is 12℃, the specific value is determined according to the system process requirement.

[0059] Preferably, in the specific technical implementation of step 412: the heat exchanger flow characteristic description and heat exchange characteristic description (generated in step 32) in the digital twin model framework of the circulating water system are taken as the processing object, the circulating water pump outlet target flow is first extracted from the key equipment target running data set, combined with the pipe network topology (generated in step 22) in the digital twin model framework of the circulating water system, the flow is distributed according to the “pipeline branch pipe diameter ratio” (for example, the main pipe is divided into DN200 and DN150 two branch pipes, and the flow is distributed according to the pipe diameter square ratio), and the initial circulating water flow of each heat exchanger is obtained; then the flow passage cross-sectional area of each heat exchanger (calculated from the tube diameter and the number of tubes, flow passage cross-sectional area = number of tubes × π × (tube diameter / 2) 2 ) is extracted from the key equipment physical parameters generated in step 1, the initial circulating water flow of each heat exchanger is divided by its flow passage cross-sectional area, and the initial flow velocity estimation value of each heat exchanger is obtained; finally, the initial circulating water flow, the initial flow velocity estimation value and the corresponding heat exchanger identification number are associated to generate an initial flow velocity-flow correlation table. This technology is different from the traditional method of distributing flow according to the number of equipment. By combining the pipe diameter ratio of the pipe network topology to distribute the flow, the initial flow velocity estimation value is more consistent with the actual pipe network flow rule, and the reliability of the estimation result is improved. For example, the circulating water pump outlet target flow is 800 m 3 / h, the main pipe is divided into DN200 (connected to heat exchanger E-101) and DN150 (connected to heat exchanger E-102) two branch pipes, and the flow is distributed according to the pipe diameter square ratio (200 2 :150 2 =16:9), the initial circulating water flow of E-101 is 800×16 / 25=512 m 3 / h, and the initial circulating water flow of E-102 is 800×9 / 25=288 m 3 / h; the flow passage cross-sectional area of E-101 is 300 roots × π × (0.032 m / 2) 2 ≈0.241 m 2 , and the initial flow velocity estimation value = 512 m 3 / h ÷ 3600 s / h ÷ 0.241 m 2 ≈0.59 m / s (the tube diameter is generally taken as 15-50 mm, and 32 mm is taken here).

[0060] Preferably, the specific implementation process of step 413 is as follows: taking the initial flow rate-flow correlation table, the pipe network topology in the digital twin model framework of the circulating water system (generated in step 22) as the processing object, first determine the pipe line position type of each heat exchanger in the pipe network, divided into three categories of “main pipe direct connection type”, “branch pipe end type” and “multi-branch series type”; set the flow rate correction coefficient for different position types: the main pipe direct connection type has smaller pressure loss along the way, the correction coefficient is taken as 0.95-1.05, the branch pipe end type has larger pressure loss along the way (the pipe resistance needs to be compensated), the correction coefficient is taken as 1.05-1.15, and the multi-branch series type is taken as 1.10-1.20; multiply the initial flow rate estimation value of each heat exchanger by the correction coefficient of its corresponding pipe line position to obtain the flow rate estimation value of each heat exchanger; update the flow rate estimation value to the initial flow rate-flow correlation table to form the corrected flow rate-flow correlation table. This technology is different from the traditional way of not considering the pipe line position and directly using the initial flow rate, by combining the pressure loss characteristics of the pipe line position to set the correction coefficient, so that the flow rate estimation value is closer to the actual running flow rate state, and the deviation caused by the position factor is reduced. For example, the heat exchanger E-101 is located at the main pipe direct connection type position, the correction coefficient is taken as 1.02, the initial flow rate estimation value is 0.59 m / s, and the corrected flow rate estimation value = 0.59 m / s x 1.02 ≈ 0.60 m / s; the heat exchanger E-102 is located at the branch pipe end type position, the correction coefficient is taken as 1.12, the initial flow rate estimation value is 0.42 m / s (calculated from 288 m 3 / h ÷ 3600 ÷ 0.231 m 2 ), and the corrected flow rate estimation value = 0.42 m / s x 1.12 ≈ 0.47 m / s.

[0061] Preferably, in a scenario, step 414 is specifically implemented as follows: taking the modified flow rate-flow volume correlation table, the key equipment target operation data set, and the heat exchanger heat transfer characteristic description in the digital twin model framework of the circulating water system (generated in step 32) as the processing objects, first extract the cold and hot side target inlet temperature of each heat exchanger and the process side target heat load from the key equipment target operation data set, and combine the heat transfer area correction logic (calculated from the number of baffles and shell diameter) in the heat exchanger heat transfer characteristic description to calculate the theoretical heat transfer characteristic value of each heat exchanger (theoretical heat transfer temperature difference = process side target heat load ÷ (initial circulating water flow rate × circulating water specific heat capacity × circulating water density)); then substitute the flow rate estimation value of each heat exchanger into the heat transfer characteristic description to determine whether the actual heat transfer capacity at this flow rate can meet the theoretical heat transfer temperature difference (if the deviation between the actual heat transfer temperature difference and the theoretical heat transfer temperature difference is within ±20%, it is determined to be matched; otherwise, the flow rate estimation value needs to be fine-tuned); the flow rate estimation value after matching is passed is defined as the effective flow rate estimation value; finally, arrange the equipment identification number, effective flow rate estimation value, theoretical heat transfer characteristic value, and matching result of each heat exchanger in the format of "equipment identification number-effective flow rate estimation value-theoretical heat transfer temperature difference-matching state" to generate the flow rate detection result of each heat exchanger. This technology is different from the traditional method of determining the rationality only based on the flow rate value. By combining the heat transfer characteristics to verify the matching degree of flow rate and heat transfer demand, it ensures that the effective flow rate estimation value meets both the flow requirement and the heat transfer demand, avoiding the problem of "flow rate qualified but heat transfer insufficient". For example, the process side target heat load of heat exchanger E-101 is 500 kW, the circulating water specific heat capacity is 4.186 kJ / (kg•℃), and the density is 1000 kg / m 3 . The theoretical heat transfer temperature difference = 500000 W ÷ (512 m 3 / h ÷ 3600 s / h × 4186 J / (kg•℃) × 1000 kg / m 3 ) ≈ 0.86 ℃, the actual heat transfer temperature difference calculation value is 0.82 ℃, the deviation is -4.7%, it is determined to be matched, and the effective flow rate estimation value is 0.60 m / s, which is included in the flow rate detection result.

[0062] Optionally, based on the determined influence dimension of the heat exchanger inter-flow rate correlation, the digital twin model representing the fluid flow characteristics and heat transfer characteristics is simulated to generate a heat exchanger inter-flow rate correlation influence matrix as the heat exchanger inter-flow rate correlation analysis result, specifically as follows:

[0063] Step 421, based on the determined influence dimension of the heat exchanger inter-flow rate correlation, simulate the circulating water flow rate change of one heat exchanger as a target heat exchanger in the digital twin model representing the fluid flow characteristics and heat transfer characteristics, and record the flow rate change amplitude and heat transfer load change amplitude of another heat exchanger as a correlation heat exchanger;

[0064] Step 422, based on the ratio of the flow rate variation range of the associated heat exchanger to the heat exchange load variation range of the target heat exchanger, the flow rate-flow rate correlation influence coefficient is calculated;

[0065] Step 423, according to the flow rate-flow rate correlation influence coefficient simulated by all heat exchangers in pairs, a flow rate correlation influence matrix between heat exchangers is generated, the row of the matrix represents the target heat exchanger number in the circulating water system as the influence source, the column of the matrix represents the associated heat exchanger number in the circulating water system as the affected object, and the element at the intersection of the row and the column represents the flow rate-flow rate correlation influence coefficient calculated when the target heat exchanger in the corresponding row is the influence source and the associated heat exchanger in the corresponding column is the affected object.

[0066] Preferably, the specific implementation process of step 421 is as follows: first, determine the influence dimension of the flow rate correlation between heat exchangers, which is explicitly the corresponding relationship between “target heat exchanger circulating water flow variation” and “associated heat exchanger flow rate variation, associated heat exchanger heat exchange load variation”, which is based on the correlation of the circulating water system pipe network, that is, the flow distribution of heat exchangers in the same branch pipe network or common trunk pipe network is mutually restricted, which is different from the traditional simulation method without clear correlation dimension; taking the digital twin model representing the fluid flow characteristics and heat exchange characteristics as the processing object, all heat exchangers in the circulating water system are selected from the model, and one of the heat exchangers is selected as the target heat exchanger (such as heat exchanger E-101) according to the principle of “selection one by one, simulation one by one”; in the digital twin model representing the fluid flow characteristics and heat exchange characteristics, the circulating water flow variation of the target heat exchanger is simulated according to the general proportion (usually ±5%~±15% of the design flow rate, the specific proportion is set according to the system stability requirement), for example, the design circulating water flow rate of E-101 is adjusted from 200m 3 / h to 220m 3 / h, or from 184m 3 / h; synchronizing the heat exchangers in the same pipe network branch or sharing the main pipe with the target heat exchanger from the model as the associated heat exchanger (such as heat exchanger E-102 sharing DN300 main pipe with E-101), recording the flow rate data of the associated heat exchanger before and after the change of the target heat exchanger flow (such as the flow rate of E-102 changes from 1.2 m / s to 1.08 m / s) and the heat exchange load data (such as the heat exchange load of E-102 changes from 450 kW to 405 kW); according to the recorded data, the flow rate change amplitude of the associated heat exchanger (such as (1.08-1.2) / 1.2x100%=-10%) and the heat exchange load change amplitude (such as (405-450) / 450x100%=-10%) are calculated, and the "target heat exchanger number, target heat exchanger flow change amplitude, associated heat exchanger number, associated heat exchanger flow rate change amplitude, associated heat exchanger heat exchange load change amplitude" are arranged into a single set of heat exchanger association simulation record table, which is the direct data source for step 422 to calculate the coefficient.

[0067] Preferably, in the specific technical implementation of step 422: taking the single set of heat exchanger association simulation record table as the processing object, extracting the two core data of the associated heat exchanger flow rate change amplitude and the target heat exchanger heat exchange load change amplitude from it-need to be clear that the target heat exchanger heat exchange load change amplitude is derived from the change of the circulating water flow (because the change of the circulating water flow will change the degree of turbulence in the heat exchanger, and then affect the heat transfer efficiency, leading to the change of the heat exchange load, such as the increase of 10% of the target heat exchanger flow, its heat exchange load usually increases by 5%-12%); the two extracted data are subjected to ratio calculation, i.e. flow rate-flow rate association influence coefficient=associated heat exchanger flow rate change amplitude / target heat exchanger heat exchange load change amplitude, the reason for the design of this calculation logic is that the final influence of the change of the target heat exchanger flow is reflected in the change of its heat exchange load, and the flow rate response of the associated heat exchanger is the direct feedback to the change of the heat exchange load, and through the ratio, the percentage of the change of the flow rate of the associated heat exchanger when the heat exchange load of the target heat exchanger changes by 1% can be quantified; after the calculation, the "flow rate-flow rate association influence coefficient" field is supplemented in the single set of heat exchanger association simulation record table, for example, when the associated heat exchanger flow rate change amplitude is-10% and the target heat exchanger heat exchange load change amplitude is 10%, the coefficient is-1.0; the above extraction, calculation and supplement operations are repeated for all "target heat exchanger- associated heat exchanger" combinations in the system that have completed simulation, generating a plurality of heat exchanger flow rate-flow rate association influence coefficient tables, which need to ensure that each coefficient corresponds to a unique "target heat exchanger- associated heat exchanger" combination to avoid duplication or omission.

[0068] Preferably, in a scenario, step 423 is specifically implemented: taking multiple sets of heat exchanger flow rate-flow rate correlation influence coefficient tables as the processing object, first sorting out the unique identification numbers (such as E-101, E-102, E-103…E-n) of all heat exchangers in the circulating water system, and taking these numbers as the rows and columns of the matrix respectively - the rows of the matrix represent the target heat exchanger numbers in the circulating water system as the influence source, and the columns of the matrix represent the associated heat exchanger numbers in the circulating water system as the affected object; from the multiple sets of heat exchanger flow rate-flow rate correlation influence coefficient tables, extract each set of "target heat exchanger number- associated heat exchanger number-flow rate-flow rate correlation influence coefficient" data, fill the coefficients into the corresponding "target heat exchanger number row, associated heat exchanger number column" intersection position of the matrix, if a certain "target heat exchanger- associated heat exchanger" combination does not produce obvious correlation (such as belonging to independent pipe networks, the flow rate change amplitude is less than 0.5%), then fill 0 in the intersection position, which represents no significant influence; after filling is completed, integrity check is performed on the matrix to check whether there is a "target heat exchanger- associated heat exchanger" combination without filling the coefficient, if there is, return to step 421 for supplementary simulation; after the check passes, generate the circulating water system heat exchanger inter-flow rate correlation influence matrix, the core value of this matrix is to structure the scattered coefficients, and the technical personnel can directly query the correlation influence degree of any two heat exchangers through the matrix, for example, the element of "E-101 row, E-102 column" in the matrix is -1.0, which means that when E-101 is the target heat exchanger, the flow rate of E-102 will change in the opposite direction by 1% for every 1% change in the heat exchange load, this matrix is the heat exchanger inter-flow rate correlation analysis result, which directly supports the optimization strategy generation of step 5.

[0069] On the basis of the above-mentioned embodiments, the application further provides a method for determining an optimization strategy of a circulating water system based on a digital twin model, which comprises:

[0070] Step 1: obtaining a circulating water system flow description file and analyzing it to determine the topological structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, wherein the key equipment at least includes heat exchangers, circulating water pumps and cooling towers;

[0071] Step 2: constructing a digital twin model framework for the circulating water system based on the topological structure of the circulating water system and the physical parameters of the key equipment in the circulating water system;

[0072] Step 3: establishing a description of the fluid flow and heat exchange in each heat exchanger and loading it onto the digital twin model framework of the circulating water system to form a digital twin model representing the fluid flow characteristics and heat exchange characteristics;

[0073] Step 4, based on the digital twin model characterizing the fluid flow characteristics and heat exchange characteristics, fluid flow and heat exchange simulation is performed to estimate the fluid flow rate inside each heat exchanger in the circulating water system to generate the flow rate detection results of each heat exchanger, and to estimate the mutual influence degree of flow rate between heat exchangers to generate the flow rate correlation analysis results between heat exchangers;

[0074] Step 5, based on the flow rate detection results of each heat exchanger and the flow rate correlation analysis results between heat exchangers, combined with the set flow rate threshold and temperature rise matching relationship for the circulating water system, an optimization strategy for the circulating water system is generated.

[0075] Optionally, step 5, based on the flow rate detection results of each heat exchanger and the flow rate correlation analysis results between heat exchangers, combined with the set flow rate threshold and temperature rise matching relationship for the circulating water system, an optimization strategy for the circulating water system is generated, specifically including:

[0076] Step 51, based on the flow rate detection results of each heat exchanger and the flow rate correlation analysis results between heat exchangers, and the cold and hot side temperature rise data of the heat exchanger, combined with the set flow rate threshold and temperature rise matching relationship, each heat exchanger is classified to obtain a classification result, the classification result is "flow rate too high - heat exchange load insufficient type" or "flow rate too low - fouling risk type";

[0077] Step 52, according to the classification result, a heat exchanger flow rate-temperature rise problem classification list is generated, which records the unique identification number of each heat exchanger, the effective flow rate estimation value in the flow rate detection result, the corresponding cold and hot side temperature rise data, and the classification result;

[0078] Step 53, according to the heat exchanger flow rate-temperature rise problem classification list, by adjusting at least one of the branch pipe diameter or the number of columns or the number of tube passes, an optimization strategy for the circulating water system is generated.

[0079] Preferably, the specific implementation process of step 51 is as follows: the "flow rate detection results of each heat exchanger" generated in step 414, the "inter-heat exchanger flow rate correlation influence matrix" (i.e. the inter-heat exchanger flow rate correlation analysis result) generated in step 423, and the "heat exchanger cold and hot side temperature rise data" collected in real time by the circulating water system are taken as joint processing objects; first, set the flow rate threshold value and temperature rise matching relationship for the circulating water system (the flow rate threshold value is distinguished according to the tube side and the shell side, the tube side flow rate threshold value is generally set to 1.0-1.5 m / s, and the shell side flow rate threshold value is generally set to 0.3-0.8 m / s; the temperature rise matching relationship is set to "when the flow rate is higher than the upper limit of the tube side, the corresponding temperature rise needs to be no less than the lower limit of the design temperature rise, and when the flow rate is lower than the lower limit of the tube side, the corresponding temperature rise needs to be no higher than the upper limit of the design temperature rise", and the design temperature rise range is generally set to 5-15°C); for each heat exchanger, perform the following determination: first, extract the effective flow rate estimation value in the flow rate detection result of the heat exchanger and the cold and hot side temperature rise data, if the effective flow rate estimation value is greater than the upper limit of the tube side flow rate and the temperature rise is less than the lower limit of the design temperature rise, it is preliminarily determined as "high flow rate - insufficient heat exchange load type", then the correlation influence coefficient when the heat exchanger is taken as the affected object is queried through the inter-heat exchanger flow rate correlation influence matrix, if the absolute value of the correlation influence coefficient is less than 0.3 (the general low influence threshold value), it is confirmed that the classification will not cause significant disturbance to the associated equipment due to subsequent adjustment, and the classification result is finally determined; if the effective flow rate estimation value is less than the lower limit of the tube side flow rate and the temperature rise is greater than the upper limit of the design temperature rise, it is preliminarily determined as "low flow rate - fouling risk type", and the correlation influence matrix is queried in the same way, and the classification result is determined after confirming that there is no significant correlation disturbance; after the determination of all heat exchangers is completed, a "heat exchanger classification result table" is generated. This technology is different from the traditional classification method based on only single equipment parameters, and by incorporating correlation influence prediction, the probability of causing associated equipment abnormalities due to subsequent optimization and adjustment can be reduced, and the system adaptability of the classification result can be improved. For example, the effective flow rate of a certain heat exchanger is 1.8 m / s (higher than the upper limit of 1.5 m / s), and the temperature rise is 4°C (lower than the lower limit of 5°C), and the correlation influence matrix shows that the influence coefficient of all associated heat exchangers is 0.2, which confirms that the determination is "high flow rate - insufficient heat exchange load type".

[0080] Preferably, in the specific technical implementation of step 52: take the "each heat exchanger classification result table" generated in step 51 as the core processing object, and integrate the data in the structured field format of "unique identifier-effective flow rate-temperature rise data-classification result"; among them, "unique identifier" adopts the rule of "equipment type-area code-number" (such as "heat exchanger-E-001" represents E area 001 heat exchanger), which ensures that each heat exchanger can be accurately located; "effective flow rate" is directly extracted from the effective flow rate estimation value (2 decimal places are reserved) in the flow rate detection result; "temperature rise data" records the average value of the inlet temperature difference and outlet temperature difference of the cold and hot sides of the heat exchanger; "classification result" clearly marks "flow rate too high-heat exchange load insufficient type" or "flow rate too low-scale risk type"; the integration process needs to check the data integrity (check whether there are missing effective flow rate or temperature rise data entries), and generate "heat exchanger flow rate-temperature rise problem classification list" after passing the verification; the list needs to be indexed and associated with the "heat exchanger flow rate correlation influence matrix" in step 423 (the unique identifier of each heat exchanger in the list corresponds to the equipment number in the matrix), which provides a direct data link for step 53 to evaluate the correlation influence. This technology is different from the traditional unstructured problem recording method. Through the index binding of the structured list and the correlation matrix, the data calling efficiency during subsequent optimization adjustment can be greatly improved, and data matching deviation can be avoided. For example, the "heat exchanger-E-001" entry in the list is recorded as "E-001-1.8m / s-4℃-flow rate too high-heat exchange load insufficient type", and is associated with "row / column number E001" in the correlation matrix through "E-001".

[0081] Preferably, in a scenario, step 53 is specifically implemented: taking the "heat exchanger flow rate-temperature rise problem classification list" and the associated "heat exchanger inter-flow rate correlation influence matrix" as the collaborative processing object; first, for different classification results in the list, match the basic adjustment mode ("flow rate too high-heat exchange load insufficient type" matches "narrow branch pipe diameter" and "reduce the number of tube rows" two basic modes, "flow rate too low-scaling risk type" matches "expand branch pipe diameter" and "increase tube row number" two basic modes); taking a "flow rate too high-heat exchange load insufficient type" heat exchanger (such as E-001) as an example, first determine the preliminary adjustment direction as narrowing the branch pipe diameter, extract its current branch pipe diameter (the general value range is DN80-DN200, and the specific value is DN150) from the list, and calculate the preliminary adjustment parameter (narrowing by 20% to DN120) according to the general adjustment amplitude (10%-20%); then, through the associated matrix, query all associated heat exchangers (such as E-002, E-003) and associated influence coefficients (E-001 to E-002 coefficient 0.6, to E-003 coefficient 0.4) when E-001 is the source of influence, calculate the flow rate change of the associated heat exchanger (E-002 flow rate change=E-001 pipe diameter adjustment induced flow rate change rate x 0.6, E-001 pipe diameter from DN150 to DN120, flow rate change rate is about-36%, then E-002 flow rate change≈-21.6%); if the original effective flow rate of E-002 is 1.2 m / s, the adjusted flow rate is about 0.94 m / s (lower than the lower limit of 1.0 m / s tube row), then the branch pipe diameter of E-002 needs to be adjusted (from DN120 to DN130) to compensate for the loss of flow rate; integrate "DN150 to DN120" of E-001 and "DN120 to DN130" of E-002 into a collaborative adjustment scheme, input the "digital twin model representing the flow characteristics and heat transfer characteristics of the fluid" generated in step 3 for simulation verification; if the simulation result shows that the flow rate of E-001 decreases to 1.4 m / s (within the threshold of 1.0-1.5 m / s), the flow rate of E-002 rises to 1.05 m / s (within the threshold), and the temperature rise of both is restored to the range of 5-15°C, then the collaborative adjustment scheme is determined as an effective optimization strategy; repeat the above "match basic mode-evaluate associated influence-collaborative adjustment-simulation verification" process for all problem heat exchangers in the list, and finally integrate all effective schemes to generate a "circulating water system overall optimization strategy document". This technology is different from the traditional single-device isolated adjustment method. Through the collaborative logic of "basic adjustment + associated compensation", the system-level flow rate and temperature rise can be overall qualified, and the associated equipment abnormal problems caused by traditional adjustment can be avoided.

[0082] In the above scheme, considering that the heat exchanger, circulating water pump and cooling tower are three key devices supporting the system core function and directly determining the optimization effect of the heat exchanger, the heat exchanger is the core target carrier of system optimization. The essence of the optimization of the present scheme is to solve the problems of unreasonable flow rate of the heat exchanger (too high to increase energy consumption, too low to cause fouling and corrosion) and insufficient heat exchange efficiency. All optimization actions ultimately point to the heat exchanger - the flow rate in the heat exchanger needs to be controlled accurately to balance the heat exchange effect and the service life of the heat exchanger. Therefore, the heat exchanger is the direct object of optimization and the core anchor point of the whole scheme, and must be included as a key device. Secondly, the circulating water pump is the power basis for the optimization of the heat exchanger. The flow rate of the fluid in the heat exchanger is driven by the circulating water flow provided by the circulating water pump: the outlet flow and pressure of the circulating water pump directly determine the initial water quantity entering each heat exchanger, and then affect the initial value of the flow rate of the heat exchanger. If the parameters of the circulating water pump are not controlled, the reasonable flow distribution logic cannot be determined, and the flow rate of the heat exchanger cannot be accurately estimated or adjusted, and the core optimization of the heat exchanger loses the data support and execution premise. Finally, the cooling tower is the cooling guarantee for the optimization of the heat exchanger. The heat exchange effect of the heat exchanger depends on the closed loop of "circulating water heat absorption-cooling tower cooling-circulating water reheat absorption": the cooling tower controls the circulating water temperature in a reasonable range (such as 30-35℃) through cooling. If the cooling effect of the cooling tower is insufficient, the circulating water inlet temperature is too high, which will cause the temperature difference between the cold and hot sides of the heat exchanger to decrease and the heat exchange load to decrease - even if the flow rate of the heat exchanger is adjusted to the theoretically reasonable value, the expected heat exchange effect cannot be achieved due to the problem of the inlet water temperature, and finally the optimization of the heat exchanger fails.

[0083] The above only describes the preferred embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various changes and modifications to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for calculating the flow velocity of a heat exchanger in a circulating water system based on a digital twin model, characterized in that, The method comprises the following steps: Step 1, obtaining a circulating water system flow description file and parsing it to determine the topology of the circulating water system and the physical parameters of the key equipment in the circulating water system, wherein the key equipment at least comprises a heat exchanger, a circulating water pump and a cooling tower; Step 2, constructing a digital twin model framework for the circulating water system based on the topology of the circulating water system and the physical parameters of the key equipment in the circulating water system; Step 3, establishing a description of fluid flow and heat exchange in each heat exchanger and loading it into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat exchange characteristics; Step 4, based on the digital twin model representing fluid flow characteristics and heat exchange characteristics, simulating fluid flow and heat exchange, estimating the fluid flow rate inside each heat exchanger in the circulating water system to generate flow rate detection results of each heat exchanger, and estimating the mutual influence degree of flow rate between heat exchangers to generate flow rate correlation analysis results between heat exchangers; Wherein, step 4 specifically comprises: Step 41, determining the target operation data of each key equipment in the circulating water system, including fluid flow related target data and heat exchange related target data, to call the fluid flow characteristic description and heat exchange characteristic description of each heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, calculate the initial flow rate estimate and correct it to obtain the flow rate estimate and generate the flow rate detection results of each heat exchanger accordingly; Step 42, based on the determined influence dimension of the flow rate correlation between heat exchangers, performing pairwise correlation simulation in the digital twin model representing fluid flow characteristics and heat exchange characteristics to generate a flow rate correlation influence matrix between heat exchangers as the flow rate correlation analysis result between heat exchangers.

2. The method of claim 1, wherein, Step 1, obtaining a circulating water system flow description file and parsing it to determine the topology of the circulating water system and the physical parameters of the key equipment in the circulating water system, wherein the key equipment at least comprises a heat exchanger, a circulating water pump and a cooling tower, specifically: obtaining a circulating water system flow description file and parsing it according to the equipment range of the extracted physical parameters to extract the physical parameters of the key equipment, the pipe network arrangement information, the connection relationship information of the key equipment and the medium flow path information to generate the topology of the circulating water system, and marking the physical parameters of the key equipment on the topology.

3. The method of claim 2, wherein, Obtaining a circulating water system flow description file and parsing it according to the equipment range of the extracted physical parameters to extract the physical parameters of the key equipment, the pipe network arrangement information, the connection relationship information of the key equipment and the medium flow path information to generate the topology of the circulating water system, and marking the physical parameters of the key equipment on the topology, specifically comprising: Step 11, obtaining a circulating water system flow description file and parsing it according to the equipment range of the extracted physical parameters to extract the physical parameters of the key equipment, the pipe network arrangement information, the connection relationship information of the key equipment and the medium flow path information; Step 12, generating static topology features and dynamic correlation description features according to the pipe network arrangement information, the connection relationship information of the key equipment and the medium flow path information; Step 13, according to the static topology characteristics and dynamic association description characteristics, a circulating water system topology association matrix is constructed, the rows of the matrix represent the topology node identification number, the columns represent the identification number of the key equipment, and the elements at the intersection of the rows and columns are the association state values; Step 14, according to the circulating water system topology association matrix, the topology structure of the circulating water system is generated, and the physical parameters of the key equipment are marked on the topology structure.

4. The method of claim 1, wherein, Step 2, based on the topology structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, a digital twin model framework for the circulating water system is constructed, specifically: according to the topology structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, a key equipment physical parameter-topology node mapping table is established to construct the digital twin model framework of the circulating water system.

5. The method of claim 4, wherein, According to the topology structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, a key equipment physical parameter-topology node mapping table is established to construct the digital twin model framework of the circulating water system, specifically including: Step 21, according to the topology structure of the circulating water system and the physical parameters of the key equipment in the circulating water system, a key equipment physical parameter-topology node mapping table is established; Step 22, based on the key equipment physical parameter-topology node mapping table, the pipe network topology form is restored and the physical parameters of each key equipment are associated to the corresponding topology node to generate a circulating water system topology framework; Step 23, for different types of key equipment, a dedicated model module is built and integrated into the circulating water system topology framework to form a digital twin model framework of the circulating water system.

6. The method of claim 1, wherein, Step 3, the description of fluid flow and heat exchange in each heat exchanger is established and loaded into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat exchange characteristics, specifically: According to the description rules of fluid mass conservation, fluid motion resistance, and heat transfer, the description of fluid flow and heat exchange in each heat exchanger is established and loaded into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat exchange characteristics.

7. The method of claim 6, wherein, According to the description rules of fluid mass conservation, fluid motion resistance, and heat transfer, the description of fluid flow and heat exchange in each heat exchanger is established and loaded into the digital twin model framework of the circulating water system to form a digital twin model representing fluid flow characteristics and heat exchange characteristics, specifically including: Step 31, obtain the description rules of fluid mass conservation, fluid motion resistance, and heat transfer, and define the physical meaning and value range of the variables in each rule to generate a fluid flow-heat exchange basic description rule and variable definition table; Step 32, according to the fluid flow-heat exchange basic description rule and variable definition table, the pipe resistance characteristics, the heat transfer characteristics corresponding to the corrected heat transfer area, and the fluid distribution flow of each pipe are calculated to establish the description of fluid flow and heat exchange in each heat exchanger; Step 33, access the heat exchanger characteristic loading interface in the digital twin model framework of the circulating water system to load the description of fluid flow and heat exchange in each heat exchanger.

8. The method of claim 1, wherein, Step 41, determine the target operation data of each key equipment in the circulating water system, including fluid flow related target data and heat exchange related target data, to call the fluid flow characteristic description and heat exchange characteristic description of each heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, calculate the initial flow velocity estimation value and correct it to obtain the flow velocity estimation value and generate the flow velocity detection result of each heat exchanger, specifically including: Step 411, determine the target operation data of each key equipment in the circulating water system, including fluid flow related target data and heat exchange related target data; Step 412, call the fluid flow characteristic description and heat exchange characteristic description of each heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, calculate the initial circulating water flow rate of each heat exchanger based on the fluid flow related target data through flow distribution calculation; based on the initial circulating water flow rate of each heat exchanger, combine the flow area of the heat exchanger to obtain the initial flow velocity estimation value; Step 413, correct the initial flow velocity estimation value based on the pipeline position of the heat exchanger in the circulating water system to obtain the flow velocity estimation value; Step 414, call the heat exchange characteristic description of each heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, calculate the theoretical heat exchange characteristic value according to the target temperature of the cold and hot sides of the heat exchanger and the process side heat load, determine the matching degree of the effective flow velocity estimation value and the corresponding heat exchange related target data, and generate the flow velocity detection result of each heat exchanger.

9. The method of claim 1, wherein, Step 42, based on the determined influence dimension of the flow velocity correlation between heat exchangers, simulate in the digital twin model representing fluid flow characteristics and heat exchange characteristics to generate a flow velocity correlation influence matrix between heat exchangers as the flow velocity correlation analysis result between heat exchangers, specifically including: Step 421, based on the determined influence dimension of the flow velocity correlation between heat exchangers, simulate the circulating water flow rate change of one heat exchanger as a target heat exchanger in the digital twin model representing fluid flow characteristics and heat exchange characteristics, and record the flow velocity change amplitude and heat exchange load change amplitude of another heat exchanger as a correlation heat exchanger; Step 422, based on the ratio of the flow velocity change amplitude of the correlation heat exchanger to the heat exchange load change amplitude of the target heat exchanger, calculate the flow velocity-flow velocity correlation influence coefficient; Step 423, generate the flow velocity correlation influence matrix between heat exchangers according to the flow velocity-flow velocity correlation influence coefficients of all heat exchangers simulated in pairs, where the rows represent the target heat exchanger numbers in the circulating water system as the influence sources, the columns represent the correlation heat exchanger numbers in the circulating water system as the affected objects, and the elements at the intersection of rows and columns represent the flow velocity-flow velocity correlation influence coefficients calculated when the target heat exchanger of the corresponding row is the influence source and the correlation heat exchanger of the corresponding column is the affected object.

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