Steam network decoupling steady state optimization method, apparatus, medium, and program product

Abstract

The application discloses a steam pipe network decoupling steady-state optimization method, equipment, medium and program product, and relates to the technical field of smart city guarantee. The method comprises the following steps: determining node pressure distribution data and flow distribution data when a quality and momentum balance condition is met according to fluid distribution data of a pipe network simulation model corresponding to a physical structure and an actual working condition of a steam pipe network; determining node enthalpy data under an energy balance condition according to hydraulic elements and pipe heat loss data; determining a condensation phase change node according to the node pressure distribution data and the node enthalpy data, relating steam enthalpy of the condensation phase change node to a saturated state under current pressure; updating current fluid distribution parameters according to the determined condensation water quantity; and taking parameters of the pipe network simulation model finally reaching a dynamic balance state as operation state parameters of the steam pipe network under a target working condition. The application can solve the problem that related technologies cannot accurately determine steam pipe network parameters, and accurately determine operation state parameters of the steam pipe network.

Description

Technical Field

[0001] This application relates to the field of smart city security technology, and in particular to a method, equipment, medium and program product for decoupling steady-state optimization of steam pipeline networks. Background Technology

[0002] Steam pipelines are heat transport networks connecting boilers, heat sources, and various steam-using equipment in industrial energy systems. The distribution data of physical parameters of the transmission pipes and their connection points in a steam pipeline network provides quantitative data for steam balance analysis, pipeline heat loss assessment, and operation scheduling and optimization. However, related technologies determine the distribution data of physical parameters of the transmission pipes and connection points in a hypothetical state that differs significantly from the actual operating conditions of the steam pipeline network. This results in the final determined physical parameter distribution not accurately reflecting the actual operating status of the steam pipeline network.

[0003] Therefore, accurately determining the distribution data of physical parameters of transmission pipelines and connecting entities that match the actual operating state of the steam pipeline network is a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0004] This application provides a decoupled steady-state optimization method for steam pipeline networks, electronic equipment, computer-readable storage media, and computer program products. It can accurately determine the distribution data of physical parameters of transmission pipelines and connecting entities that match the actual operating state of the steam pipeline network. During the design phase of the steam pipeline network, it can accurately assess the actual working state of complex pipeline networks, such as ring networks and multi-source multi-sink systems, after their construction. During the operation phase, it can quickly and accurately locate the largest heat dissipation pipe section and pressure drop bottleneck of the steam system.

[0005] To address the aforementioned technical problems, this application provides a decoupled steady-state optimization method for steam pipeline networks, comprising:

[0006] Based on the physical structure, pipeline parameters, and target operating condition parameters of the steam pipeline network, a corresponding pipeline network simulation model is determined. Based on the condensate distribution and steam properties of each pipe section in the simulation model, the nodal pressure and flow distribution data that satisfy the mass and momentum balance conditions are determined as hydraulic elements. Based on the hydraulic elements and pipeline heat loss data, the nodal enthalpy data of the pipeline network simulation model under energy balance conditions are determined. Based on the nodal pressure distribution and nodal enthalpy data, the target node in the pipeline network simulation model where condensation phase change occurs is determined. The steam enthalpy of the target node is correlated to the saturation state under the current pressure. The condensate flow rate of each pipe section is determined based on the saturation state, and the current condensate distribution and steam properties are updated based on the condensate flow rate. The hydraulic elements, thermal parameters, and condensate flow rate parameters of the pipeline network simulation model under dynamic equilibrium are used as the operating state parameters of the steam pipeline network under the target operating conditions.

[0007] This application also provides an electronic device, including a memory and a processor, wherein the processor is used to implement the steps of the above-described steam pipeline decoupling steady-state optimization method when executing a computer program stored in the memory.

[0008] This application also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described steam pipeline decoupling steady-state optimization method.

[0009] Finally, this application also provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the above-described steam pipeline network decoupling steady-state optimization method.

[0010] The superiority of the technical solution provided in this application lies in the following aspects: First, a digital simulation model of the steam pipeline network is constructed. Then, the steps of determining hydraulic elements, determining thermal parameters, and phase change intervention and model updating are executed sequentially. By decoupling the highly coupled hydraulic element and thermal parameter determination processes into two sequentially executed processes, the problem of difficulty in adapting to engineering applications due to the complexity of intermediate process control is avoided. Second, condensate is removed from the mainstream steam flow as an independent mass item, and its generation is used as a key feedback signal to dynamically update the mass conservation relationship and physical property parameters in the hydraulic calculation. This dynamically corrects the pipeline mass conservation relationship and fluid property distribution, which can overcome the physical distortion problem caused by neglecting the phase change and separation of condensate in traditional homogeneous flow models. Stable closed-loop feedback iteration is achieved using the condensate volume, effectively avoiding numerical instability, divergence, or convergence to non-linearity caused by nonlinearity and sensitivity to initial conditions in strongly coupled synchronous solutions. The physical understanding significantly enhances the numerical stability and physical consistency of multiphase flow and heat transfer coupled systems. Through alternating iterations of "hydraulic → thermal → condensate → rehydraulic" and a closed-loop iterative path of "thermal response → phase change → flow field correction," it can significantly improve the numerical stability, convergence reliability, and computational accuracy of steady-state simulation of steam pipeline networks under all operating conditions (especially low load and long-distance transport) without relying on human experience to adjust relaxation factors. It can accurately quantify and characterize the intrinsic equilibrium state of steam pipeline networks under specific operating conditions, and accurately determine the physical parameter distribution data of transmission pipelines and connecting entities that match the actual operating state of steam pipeline networks. Ultimately, it enables accurate pre-assessment of the actual operating state of complex pipeline networks, such as ring networks and multi-source multi-sink systems, during the steam pipeline network design phase; and during the operation phase, it can quickly and accurately locate the largest heat dissipation pipe section and pressure drop bottleneck of the steam system.

[0011] Furthermore, this application also provides corresponding electronic devices, computer-readable storage media, and computer program products for the decoupling steady-state optimization method of steam pipeline networks, further making the method more practical. The electronic devices, computer-readable storage media, and computer program products have corresponding advantages. Attached Figure Description

[0012] The following is a brief introduction to the drawings used in this application. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0013] Figure 1 This is a flowchart illustrating a decoupling steady-state optimization method for a steam pipeline network provided in this application.

[0014] Figure 2 A flowchart illustrating another decoupling steady-state optimization method for steam pipeline networks provided in this application.

[0015] Figure 3 This is a schematic diagram showing the uniform mixing of the enthalpy of the upstream node and its flow into the downstream pipeline, as provided in this application.

[0016] Figure 4 This is a schematic diagram of the temperature distribution inside the pipes of the steam pipeline network provided in this application, within an exemplary application scenario.

[0017] Figure 5 This is a schematic diagram of the pressure distribution inside the steam pipeline network provided in this application in an exemplary application scenario.

[0018] Figure 6 This is a schematic diagram of the mass flow rate distribution inside the pipes of the steam pipeline network provided in this application, within an exemplary application scenario.

[0019] Figure 7 This is a structural diagram of an exemplary embodiment of the electronic device provided in this application. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions of this application, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. The terms "comprising" and "having," and any variations thereof, in the specification and the aforementioned drawings are intended to cover non-exclusive inclusion. The term "exemplary" means "serving as an example, embodiment, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as superior to or better than other embodiments.

[0021] Steam pipelines are thermal transport networks connecting boilers, heat sources, and various steam-using equipment in industrial energy systems. As a component of the steam system and a material transport channel, their operational performance directly affects the production efficiency, energy utilization rate, and carbon emissions of the industrial energy system. To achieve energy-saving optimization, equipment selection, and operational scheduling decision support, it is necessary to analyze the hydraulic (pressure-flow rate) and thermal (temperature-enthalpy) aspects of the steam pipeline network to determine the distribution of physical parameters for each pipe and node in the steam pipeline network model. This includes the pressure and temperature parameters of each physical node and the flow rate parameters of each pipe segment. Taking a steam system where a boiler supplies steam to two workshops as an example, the boiler outlet can be considered the source node, the steam distribution cylinder and the two workshops as nodes, and the pipes connecting the boiler, steam distribution cylinder, and workshops as pipelines. The source node is configured with steam pressure and temperature parameters, while the workshops are configured with steam flow rate requirements. Different distributions of physical parameters correspond to the positions and parameters of physical entities in the steam pipeline network under different physical layouts, determining different operating states of the steam system and providing a quantitative basis for steam balance analysis, pipe loss assessment, and energy-saving retrofitting. For example, before constructing an industrial energy system, analyzing the distribution of physical parameters of each pipe and node in a steam network model can determine the types of physical equipment corresponding to the steam network. This includes selecting matching pipe sizes based on expected flow rate and allowable pressure drop, determining the required pressure for pumps and compressors based on network resistance, and selecting boilers, pressure reducing and desuperheating devices, and safety valves based on various pressure data. During the operation of the industrial energy system, when a fault occurs, fault diagnosis can be performed by analyzing the steam network's flow rate, pressure, and temperature to determine steam balance and network heat loss.

[0022] In determining the distribution of physical parameters of each pipe and physical node in a steam pipeline network, one related technique assumes that all steam in the network is superheated and does not undergo phase change, and simplifies the steam's physical properties. Another related technique employs a non-isothermal steady-state approach, using the Runge-Kutta integral method for coupled calculations of the pipeline network, while simultaneously using a data-driven approach to correct simulation results, forming a data model jointly driven by both data and physical models. However, its verification network is relatively small, and due to the limitation that the computational logic topology must be a branched network, the accuracy improvement after adding the data model is not significant. Furthermore, a large amount of unreasonable data collection exists in actual operating conditions, making data training unsupported. Yet another related technique supplements the continuity equation by removing condensate volume and employs PISO (Pressure Implicit with Splitting of Operators) and the finite volume method, but it does not specify the method for calculating pipeline condensate volume or perform iterative updates to the condensate volume calculation. Another related technology constructs a misaligned mesh based on the removal of condensate and the finite volume method, and uses the simple (Semi-Implicit Method for Pressure-Linked Equations) to determine the final result. This method uses a homogeneous model or a simplified two-phase flow model in the iterative process, which is insufficient in modeling the condensate generation and removal process and is difficult to accurately reflect the actual working conditions.

[0023] However, during steam transportation, continuous phase changes occur due to heat dissipation in pipelines and heat exchange in equipment, resulting in a large amount of condensate. The coexistence and dynamic separation of gas and liquid phases make the steam pipeline network a complex system with strong nonlinearity and multiphase coupling. If a homogeneous flow model is used to determine the physical parameter distribution of each pipeline and node, treating the mixture of steam and condensate as a single homogeneous phase and determining it using equivalent density and equivalent enthalpy, this method simplifies the calculation process. However, because it ignores the actual behavior of condensate separating from the mainstream as an independent liquid phase and being discharged by the drain valve, the mass and energy conservation relationships used in the parameter determination process will be distorted. For applications involving long-distance transportation, low-load operation, or multi-stage drain systems, errors will accumulate significantly, leading to a final physical parameter distribution that deviates severely from reality and making it impossible to accurately determine the physical parameter distribution of each pipeline and node. Furthermore, the hydraulic and thermodynamic equations of steam pipe networks are highly coupled. Pressure distribution affects flow velocity and heat dissipation, while temperature changes in turn affect steam density and viscosity, thus altering pressure drop characteristics. If synchronous coupling is used, the hydraulic and thermodynamic variables are iterated together. However, in complex ring-shaped pipe networks or scenarios with multiple sources and sinks, this method may lead to divergent solutions or convergence to non-physical solutions due to sensitivity to initial values ​​and strong nonlinearity, failing to obtain physical parameter distribution data that matches the actual situation. Although related technologies employ the finite volume method to separate the condensate phase, the finite volume method is complex to program and computationally intensive, with the aforementioned misaligned meshes further increasing the complexity of pipe network calculations. Moreover, related technologies use the simple or PISO methods for calculation, which require manual adjustment of relaxation factors to ensure computational convergence. However, in actual operating conditions, complex sensor errors, inconsistent acquisition times, and other factors make it difficult to achieve high stability.

[0024] Therefore, the relevant technologies have the following problems in determining the distribution of physical parameters of each pipe and physical node in the steam pipeline network: ignoring the condensation phase change behavior of steam during transportation, or failing to explicitly model the generation, separation, and removal of condensate water, leading to inaccurate calculations of mass and energy conservation; adopting the homogeneous flow assumption or simplifying physical properties, which weakens the applicability of the model in the wet steam region; and using strong coupling methods, resulting in complex calculations, poor convergence, and strong dependence on the pipeline network topology (e.g., limited to branched networks) or data quality, thus limiting the breadth and robustness of engineering applications.

[0025] In view of this, to address the shortcomings of related technologies in handling phase change processes, modeling the dynamic behavior of condensate, and adapting to complex pipe networks, which lead to low physical fidelity, poor computational accuracy, and difficulty in convergence of simulation models used in determining the physical parameter distribution of steam pipe networks, making it difficult to accurately reflect the hydraulic-thermal coupling characteristics under actual operating conditions, this application determines the operating state parameters of the steam pipe network under target operating conditions based on condensate phase separation and decoupling iteration. In determining the operating state parameters, the traditional homogeneous flow assumption is abandoned, and the generation, separation, and removal processes of condensate are explicitly modeled. Condensate is treated as an independent mass and energy output term, separated from the main steam flow. Based on this, hydraulic elements and thermal parameters are determined alternately through decoupling: first, the hydraulic equations are solved with a fixed temperature field; then, the thermal distribution and condensate volume are calculated based on the updated flow field, iterating until convergence. By decomposing the complex multiphase coupling problem into independently solvable sub-problems, the simulation accuracy and convergence stability are significantly improved. Meanwhile, compared to the finite volume method, this method is easier to implement mesh refinement, thus supporting detailed modeling of condensate discharge behavior from end-user steam equipment. This provides technical support for the accurate evaluation of key energy efficiency indicators such as steam utilization rate and condensate recovery rate, and can be widely applied to industrial energy-saving diagnosis, pipeline network optimization design, and operation scheduling decisions, providing data support for improving the energy efficiency of steam systems. The specific application environment architecture or hardware architecture upon which the decoupled steady-state optimization method for steam pipeline networks depends is described here. The following are examples of some possible application scenarios related to the technical solution of this application, which may include the following:

[0026] For the large industrial park's steam transmission pipeline system, steam is transported from three centralized heating boilers (steam source nodes) to 20 production workshops (steam consumption nodes). The total length of the pipeline network is 8.5 km, including a mixed topology of ring and branch networks. This system features long-distance transmission sections (the longest single section is 1.2 km) and low-load operation conditions (some workshops use only 30% of their daytime steam consumption at night). The steam transmission pipeline system deploys multiple data acquisition terminals, installed at the steam source outlet, pipeline nodes, and workshop entrances. Data on pressure (measurement range 0-4 MPa, accuracy ±0.01 MPa), temperature (measurement range 0-600 K, accuracy ±0.5 K), and flow rate (measurement range 0-50 kg / s, accuracy ±0.1 kg / s) are collected at a preset frequency, such as once per minute. The computing device for the steam transmission pipeline system can be a server: for example, an industrial-grade server configured with a processor, 128GB DDR4 memory, and 2TB SSD, used to run the pipeline simulation model and calculate parameters; the storage device for the steam transmission pipeline system can be a distributed database, for example, capable of supporting 100,000 data entries / second with a storage latency of ≤10ms, used to store pipeline physical parameters, data collected by data acquisition terminals, and simulation calculation results; the steam transmission pipeline system may also include output devices, such as an industrial control center display screen (4K resolution, supporting real-time parameter visualization) and report printing equipment, used to display pipeline operating status parameters and energy efficiency analysis results.

[0027] The system collects physical structural parameters of the pipeline network (such as pipe inner diameter, length, roughness, insulation layer thickness, etc.), equipment parameters (such as boiler rated pressure, temperature, steam flow demand in workshops, etc.), and target operating condition parameters (such as steam demand in each workshop and ambient temperature at the current time) through a data acquisition terminal. These parameters are stored in a distributed database and sent to a server. The server runs the decoupled steady-state optimization method for the steam pipeline network provided in this application to construct a pipeline network simulation model. It sequentially completes the calculation of hydraulic elements, thermal parameters, identification of condensate phase change nodes, and updating of condensate volume. After multiple iterations to reach dynamic equilibrium, it outputs parameters such as pressure, flow rate, temperature, enthalpy of each node, and condensate volume of each pipe section. These parameters are displayed in real time on the control center screen, and an energy efficiency assessment report is generated. This provides a basis for decision-making for pipeline network optimization scheduling (such as adjusting boiler output pressure and optimizing the timing of steam trap opening) and energy-saving renovation (such as strengthening insulation for high heat dissipation pipe sections).

[0028] Furthermore, in order to verify the effectiveness of the steam pipeline network decoupling steady-state optimization method of this application, this invention also uses the above-mentioned related technologies using PISO and finite volume method for verification. The results of the related technologies and the operating state parameters determined by this application are shown in Table 1.

[0029] Table 1 Results of Operating Status Parameters

[0030]

[0031] As can be seen from the above, some end nodes of the related technologies may have temperatures that are completely consistent with the steam source due to non-convergence, which is seriously inconsistent with the actual physical scenario. Apart from this, the final output results of the present invention are basically consistent with the results of the related technologies.

[0032] The various non-limiting embodiments of this application are described in detail below with reference to the accompanying drawings and specific embodiments. First, please refer to... Figure 1 According to the decoupling steady-state optimization method for steam pipeline networks provided in this application, in some embodiments of the method, the method includes the following steps:

[0033] S101: Determine the corresponding pipeline simulation model for the steam pipeline network based on the physical structure, pipeline parameters, and target operating condition parameters of the steam pipeline network.

[0034] The physical structure of the steam pipeline network includes multiple pipelines, physical equipment at both ends of the pipelines, and the connection relationships between the pipelines and the physical equipment.

[0035] Pipeline parameters describe the inherent and invariant properties of the steam network's physical structure. These can include the pipe's inner diameter, which affects steam velocity and pressure drop; the total length of the pipe for spatial discretization and calculation of total resistance and heat dissipation; the roughness of the pipe's inner wall, used to calculate the friction coefficient; insulation parameters (such as insulation material type and thickness); and pipe inclination and elevation changes (the pipe's angle and elevation difference relative to the horizontal plane), used to calculate the effect of gravity on the static head of the fluid. Target operating condition parameters refer to the input and output conditions at the steam network boundary under a specific analysis scenario. These parameters are variable and define how the system operates at a specific time. They include, but are not limited to, source parameters (such as pressure and steam temperature at the source) and sink parameters (such as mass flow rate). Changing these parameters allows for the simulation of different production scheduling schemes or load conditions. The pipeline simulation model consists of a networked topology structure composed of at least one node and at least one pipeline, based on the actual physical connection relationship of the steam pipeline network. The node, as the topological vertex, represents the connection point, source point, sink point, or status monitoring point. The pipeline, as the topological edge, connects two nodes and is the physical carrier of pressure drop and heat loss during steam flow. The node is the carrier for applying system boundary conditions and applying conservation laws. The pipeline, as the edge in the topology structure, is used to connect two nodes and is the physical carrier representing the pressure drop and heat loss during steam flow. It can simulate the hydraulic flow, heat transfer, and condensation phase change process of steam in the pipeline network.

[0036] S102: Based on the condensate distribution and steam properties of each pipe section in the pipeline network simulation model, determine the nodal pressure distribution data and flow distribution data when the mass and momentum balance conditions are met, and use them as hydraulic elements.

[0037] Among them, steam physical properties refer to a series of parameters describing the thermophysical properties of steam and varying with its state (pressure, temperature / enthalpy), such as state parameters (density, temperature, dryness fraction), transport parameters (dynamic viscosity / kinematic viscosity), energy parameters (specific enthalpy, isobaric specific heat capacity, saturation parameters), and saturation parameters such as saturation temperature and saturated steam enthalpy. These parameters are the bridge that concretizes the laws of conservation of mass, momentum, and energy. The condensate distribution and steam physical properties of each pipe section are parameters obtained from the previous round of calculations. If it is the first calculation process, the condensate in each pipe can be 0, and the steam physical properties can be referenced to the pressure steam source point and regarded as fixed values. Hydraulic elements include nodal pressure distribution data and flow distribution data, reflecting the flow equilibrium state of steam in the pipeline network.

[0038] This step, based on the condensate distribution (condensate volume in each pipe section) and steam properties (such as density) updated in the previous iteration, calculates the node pressure and flow distribution data for the entire network in the pipeline simulation model by satisfying the mass balance condition (the total mass flow rate flowing into any node equals the total mass flow rate flowing out) and the momentum balance condition (the pressure drop in the pipe section equals the sum of frictional resistance, local resistance, and gravity). The node pressure distribution data refers to the set of parameters consisting of the pressure values ​​at each node in the steam pipeline network. It represents the pressure field of the entire pipeline system, visually demonstrating the pressure attenuation from the source point (such as the boiler) to each sink point (such as the user). The flow distribution data refers to the set of mass flow rates flowing through each pipe section in the steam pipeline network, representing the path and distribution ratio of steam in the pipeline network.

[0039] S103: Based on hydraulic parameters and pipeline heat loss data, determine the nodal enthalpy data of the pipeline network simulation model under the condition of satisfying energy balance.

[0040] Among these, hydraulic elements refer to the nodal pressure and flow distribution data obtained through the above steps in the current calculation cycle. Pipeline heat loss data refers to the rate at which heat is lost from the pipe to the surrounding environment through the insulation layer due to the temperature difference between the inside and outside of the pipe as steam flows through each pipe segment, quantifying the insulation performance and energy loss of the pipe. Nodal enthalpy data refers to the set of specific enthalpy of steam at each node in the steam network. Enthalpy is a thermodynamic state parameter that can be understood as the total energy contained in a fluid, including internal energy and flow work. This step calculates the heat loss of each pipe segment based on the hydraulic elements, and then calculates the nodal enthalpy data of the entire network in the network simulation model by satisfying the energy balance condition (energy conservation of the inflow and outflow control volumes).

[0041] S104: Based on the node pressure distribution data and node enthalpy data, determine the target node in the pipeline simulation model where condensation phase change occurs, associate the steam enthalpy of the target node with the saturation state under the current pressure, determine the condensate volume of each pipe section based on the saturation state, and update the current condensate distribution and steam physical property parameters based on the condensate volume.

[0042] In this context, the target node refers to the node in the pipeline simulation model where a condensation phase change occurs. Associating the steam enthalpy of the target node with the saturation state at the current pressure means that at the identified pipeline node where condensation occurs, the pressure value of that node is forcibly associated with the saturated steam enthalpy; that is, the enthalpy of that node is set to be equal to the enthalpy of the corresponding saturated steam at the current pressure. After obtaining the enthalpy of each node through the previous step, due to the discrete errors in numerical calculations and fluctuations in the iteration process, a physically impossible state may be calculated: that is, the enthalpy of the node is lower than the saturated steam enthalpy corresponding to its current pressure. Therefore, this type of error needs to be corrected. This step corrects the enthalpy calculated in S103 based on the saturated enthalpy corresponding to the saturation state at the current pressure. That is, if the calculated enthalpy is lower than the saturated steam enthalpy, it means that in reality, some steam has condensed into water, releasing latent heat, making the state of the remaining steam exactly at the saturation line. In this embodiment, the calculated enthalpy is replaced by the enthalpy of the saturated state. Once the location and state of the phase change are determined, the mass flow rate of condensate generated due to heat dissipation within each pipe section is further determined. Thermodynamic parameters may include not only the nodal enthalpy data determined in this step, but also temperature distribution data.

[0043] This step, based on the calculated pressure and enthalpy data, identifies the target nodes where condensation phase transition occurs (i.e., nodes whose current enthalpy is lower than their saturated enthalpy at the current pressure). The enthalpy of these target nodes is then forcibly correlated to a saturated state (i.e., corrected to the saturated steam enthalpy at the current pressure). Based on this saturated state, the condensate flow rate for each pipe section is recalculated, and the condensate distribution and steam properties (such as changes in mainstream steam density due to partial steam condensation) of the entire model are updated accordingly.

[0044] S105: The hydraulic elements, thermal parameters, and condensate volume of the pipeline network simulation model are used as the operating status parameters of the steam pipeline network under the target operating conditions when they reach a dynamic equilibrium state.

[0045] In this context, dynamic equilibrium refers to a state where, in two consecutive rounds of iterative calculations, the changes in pressure at each node, mass flow rate of the pipe segment, enthalpy at each node, and condensate flow rate of the pipe segment are all less than the preset convergence threshold, and the model output parameters tend to stabilize. For example... Figure 2As shown, this application performs multiple iterative calculations on S102-104 until a dynamic equilibrium state is reached. This means the hydraulic elements, thermal parameters, and condensate flow rate of the pipeline simulation model reach a dynamic equilibrium state (i.e., the change in the results between two iterations is sufficiently small). The final parameter data is then output as the operating state parameters of the steam pipeline network under the target operating conditions. Furthermore, if there are areas in the pipeline simulation model that do not participate in the above process, such as areas without steam sources, default values ​​are used to fill in the data based on these areas to ensure the completeness of the overall results. In addition to parameters such as pressure, mass flow rate, temperature, enthalpy, and condensate distribution of each pipeline in the dynamic equilibrium state, some key information from the above calculation process can also be output, such as excessive pipeline flow velocity or calculation non-convergence.

[0046] In the technical solution provided in this application embodiment, a digital simulation model of the steam pipeline network is first constructed. Then, the steps of determining hydraulic elements, determining thermal parameters, and phase change intervention and model updating are executed sequentially. By decoupling the highly coupled hydraulic element and thermal parameter determination processes into two sequentially executed processes, the problem of difficulty in adapting to engineering applications due to the complexity of intermediate process control is avoided. Secondly, condensate is removed from the main steam flow as an independent mass item, and its generation is used as a key feedback signal to dynamically update the mass conservation relationship and physical property parameters in the hydraulic calculation. The pipeline mass conservation relationship and fluid physical property distribution are dynamically corrected, which can overcome the physical distortion problem caused by neglecting the phase change and separation of condensate in the traditional homogeneous flow model. Stable closed-loop feedback iteration is achieved by using the condensate volume, which effectively avoids numerical instability, divergence, or convergence to non-linearity caused by nonlinearity and sensitivity to initial values ​​in strongly coupled synchronous solutions. The physical understanding significantly enhances the numerical stability and physical consistency of multiphase flow and heat transfer coupled systems. Through alternating iterations of "hydraulic → thermal → condensate → rehydraulic" and a closed-loop iterative path of "thermal response → phase change → flow field correction," it can significantly improve the numerical stability, convergence reliability, and computational accuracy of steady-state simulation of steam pipeline networks under all operating conditions (especially low load and long-distance transport) without relying on human experience to adjust relaxation factors. It can accurately quantify and characterize the intrinsic equilibrium state of steam pipeline networks under specific operating conditions, and accurately determine the physical parameter distribution data of transmission pipelines and connecting entities that match the actual operating state of steam pipeline networks. Ultimately, it enables accurate pre-assessment of the actual operating state of complex pipeline networks, such as ring networks and multi-source multi-sink systems, during the steam pipeline network design phase; and during the operation phase, it can quickly and accurately locate the largest heat dissipation pipe section and pressure drop bottleneck of the steam system.

[0047] In the above embodiments, no limitation is made on how to create a digital simulation model that can accurately reflect the physical system and is suitable for calculation. This embodiment also provides an exemplary construction method for a pipeline network simulation model, which may include the following:

[0048] Based on the physical structure of the steam pipeline network, the transmission channels of the steam pipeline network are used as pipes, and the physical equipment at both ends of the transmission channels are used as nodes to construct the corresponding topology model of the steam pipeline network. According to the pipe parameters of the steam pipeline network, corresponding physical attribute parameters are configured for each pipe in the topology model, and corresponding operating boundary conditions are configured for the boundary nodes according to the operating condition parameters. The operating boundary conditions include the pressure and temperature of the source nodes and the mass flow rate of the sink nodes. Based on the operating boundary conditions, the target area containing the superheated steam source is determined in the topology model, and the pipes in each target area are discretized according to the preset length to generate the pipeline network simulation model.

[0049] Before constructing the pipeline network simulation model, the corresponding topological physical structure data and boundary point acquisition data of the steam pipeline network are read to determine isolated areas without steam sources and areas suitable for simulation. Topological data, data acquired by the data acquisition and monitoring control system, are organized and recorded to divide the pipeline network nodes and initialize unknowns. The topological structure model reflects the digital skeleton of the physical connection relationships between each pipe and node in the steam pipeline network, but does not contain specific parameter information; the physical property parameters are inherent physical parameters of the pipes, including inner diameter, length, roughness, insulation layer thickness, and thermal conductivity, which do not change with operating conditions; the operating boundary conditions are the operating parameters set for the pipeline network boundary nodes, including the pressure and temperature of the source nodes (i.e., input parameters) and the mass flow rate of the sink nodes (i.e., output parameters); the target region is an independent area in the topological structure model containing superheated steam sources, which is the effective range for simulation calculations.

[0050] For example, the physical connection information of the steam pipeline network is read and parsed, abstracting boilers, steam distribution cylinders, user equipment, etc., into nodes, and the pipes connecting these devices into pipe segments. This constructs a network skeleton that only describes the connection relationships, which is the basis for all subsequent calculations. On the established network skeleton, each pipe segment element is assigned its inherent physical properties. These parameters do not change with the simulation and are the fundamental basis for calculating the pipeline flow resistance (i.e., frictional pressure drop) and heat loss. For example, the parameters of a certain pipe segment are: an inner diameter of 0.15m, an absolute roughness of 0.000045m, and a 50mm thick rock wool insulation layer. Furthermore, operating conditions are set on the boundary nodes of the topology network. For example, the source node (such as the boiler outlet) is set to pressure and temperature, and the boundary sink node (such as the user inlet) is set to mass flow rate edge. This provides the boundary conditions for the pipeline network simulation model and defines the system's input and output.

[0051] In this embodiment, all isolated topologies that meet the basic simulation conditions are simulated, i.e., steps S102-S105 are executed. For example... Figure 2As shown, an isolated region search is first performed. If a gas source exists in this isolated region, it is used as the simulation area; otherwise, it is treated as a region without a gas source. If the steam source temperature and pressure in the simulation area are not determined to be superheated steam, this region cannot be calculated and is also considered a region without a steam source, so no simulation calculation is performed. Otherwise, it is used as the target region. The calculation of the target region first requires the establishment of a simulation grid: all pipe networks are evenly divided into several segments according to the maximum length requirement. For example, if all pipe segments within each target region are equally divided according to a preset "maximum segment length" (e.g., 20 meters), then the continuous pipeline is discretized into a series of interconnected micro-segments and nodes, forming a computational grid. At the same time, the system allocates and stores variables such as pressure, mass flow rate, and enthalpy for each node, and allocates and stores variables such as heat dissipation and condensation for each micro-segment. The pressure, velocity, mass flow rate, and enthalpy of all nodes in the entire pipeline network are established as unknowns, and parameters such as heat dissipation and condensation of each pipe segment are also established, forming the global unknown parameters of the pipeline network, which prepares for the subsequent organization of finite difference equations and parameter determination process.

[0052] As shown above, this embodiment automatically searches for independent pipeline regions (isolated areas) based on topological connections. Then, it checks whether each area contains a steam source and whether the steam source is in the form of superheated steam. Only "valid simulation areas" that simultaneously meet both conditions are processed further; invalid areas are excluded, thus saving computational resources.

[0053] After constructing the pipeline simulation model, the pipeline continuity equation, hydraulic equation, and thermal equation can be further determined. Since the pipeline length is generally much larger than its inner diameter, the flow inside the pipeline is generally simplified to one-dimensional flow, following the following governing equations:

[0054] (1)

[0055] (2)

[0056] (3)

[0057] in, This refers to the vapor density, expressed in kg / m³. The subscript 'c' indicates condensation. Indicates time, in seconds; The distance along the pipe is in meters; This refers to the steam velocity, measured in m / s. The mass of condensate per unit length and per unit area is expressed in kg / s. This is the steam pressure, measured in Pa. The pipe inclination angle; This is the friction coefficient. This refers to the inner diameter of the pipe, in meters. This refers to the internal energy of steam, expressed in J / kg. This represents the acceleration due to gravity, with a value of 9.8 m / s². This refers to the enthalpy of steam, expressed in J / kg. The elevation difference is expressed in meters. The latent heat of condensation is expressed in J / kg. This represents the heat dissipation per unit length and unit area of ​​the fluid interface in the pipe, expressed in W / s.

[0058] Due to steady-state conditions, the partial derivatives with respect to time are all zero. Since the calculations are based on pressure, enthalpy, and mass flow rate, and the steam flow area along the pipe is assumed to be constant, the above equations can be simplified to the following relationships:

[0059] (4)

[0060] (5)

[0061] (6)

[0062] Where m represents mass flow rate, with units of kg / s; The distance along the pipe is in meters; This represents the cross-sectional area of ​​the pipe, in units of... ; This indicates the mass of condensate per unit length, expressed in kg / s. This indicates the mass of condensate per unit length, expressed in kg / s. This indicates steam pressure, with the unit being Pa. This refers to the friction coefficient along the pipeline. This represents the latent heat of condensation, expressed in J / kg. This represents the heat dissipation per unit length of pipe, expressed in W / s. Equations 4-6 above require the introduction of a state equation to relate thermodynamic variables such as density, pressure, and temperature. This application can use the IAPWS-IF97 standard (calculation standard name) for calculating the thermophysical properties of water and water vapor to determine this. The pipe friction coefficient can be calculated using the Colebrook formula:

[0063] (7)

[0064] Where k represents the pipe roughness, The Reynolds number represents the flow of steam.

[0065] Heat transfer calculations can be determined based on the following relationship:

[0066] (8)

[0067] Wherein, the subscript 's' represents steam, the subscript 'a' represents the environment, and the subscript '0' represents the pipe's inner diameter and related physical quantities; the outer layer is the first layer of insulation material with a thermal conductivity of [missing value]. The outer diameter is And so on, up to the outermost layer n; K represents the heat transfer coefficient per unit length of the pipe, with units of W / (mk); This indicates the heat dissipation of the pipe, expressed in W / m. Indicates steam temperature, The temperature of the pipeline is in Kelvin (K). This represents the convective heat transfer coefficient between steam and the inner wall of the pipe, with units of W / (K·m2). It represents the convective heat transfer coefficient between the outside air and the outer wall of the pipe, with the unit being W / (K·m2); This refers to the inner diameter of the pipe, in meters. Let be the outer diameter of the i-th layer of material, in meters. This represents the thermal conductivity of the i-th layer of material, expressed in W / (m²*K).

[0068] Since the thermal resistance between the inner wall of the steel pipe and the steam is small, its impact on the overall heat dissipation calculation is negligible. Furthermore, the steel pipe itself has a high thermal conductivity and low thermal resistance, which can also be ignored.

[0069] The above embodiments do not limit how to determine the nodal pressure distribution data and flow distribution data when the mass and momentum balance conditions are met. Based on the above embodiments, this application also provides a process for treating the density of each node as constant, and iteratively determining the flow and pressure of all nodes in the pipeline network by simultaneously solving the above continuity equation and momentum equation, using the finite difference method. This process may include the following:

[0070] Based on the physical connections of the pipeline network simulation model, and assuming that the pressure at the nodes connected to each pipe segment is the same, and that the total inflow and outflow at each node are the same, the mass flow conservation condition at the nodes is determined. Using the finite difference method, with backward difference as the finite difference scheme, the pipeline continuity equation and momentum equation are discretized. Since the steam density at each node in the pipeline network simulation model is constant during one iteration, the boundary condition is set so that only one steam source node in each target region of the pipeline network simulation model is configured with pressure parameters, and the remaining nodes are configured with mass flow parameters. Based on the mass flow conservation condition, the discretized pipeline continuity equation, and the discretized momentum equation, the node pressure distribution data and flow distribution data of the pipeline network simulation model in the current iteration are determined.

[0071] The mass flow conservation condition states that the sum of the flow rates in all pipe segments flowing into a node equals the sum of the flow rates out of that node; this is a conservation law in hydraulic calculations. Backward difference is a difference scheme of the finite difference method. By calculating the derivative between the current value and the previous node value, it can better reflect the upstream influence on the downstream, ensuring numerical stability and monotonicity. The continuity equation describes the mass conservation within a pipe segment; in steady state, it simplifies to the change in mass flow rate along the pipe length equaling the condensate flow rate. The momentum equation describes the momentum conservation within a pipe segment, reflecting the relationship between pressure drop and parameters such as flow velocity and drag coefficient. The hydraulic element calculation process in this embodiment is determined based on the node mass flow conservation condition, the discretization of the pipe segment momentum balance equation, and boundary conditions. The boundary conditions refer to setting the pressure of only one steam source node within a target area, while the mass flow rates of the remaining nodes (mainly sink nodes) are given. In a single hydraulic calculation, the steam density and condensate flow rate are considered constants. By combining the above three parts, a large system of linear equations is formed. This system is then solved using sparse matrix techniques to obtain the pressure and flow distribution for the current cycle.

[0072] In this embodiment, the hydraulic equations are solved using the finite difference method, specifically backward differencing, which is implicit differencing. Backward differencing effectively reflects the upstream influence on the downstream, thus ensuring numerical stability and monotonicity, and unlike central differencing, it does not require additional boundary condition processing. However, backward differencing is only a first-order precision differencing scheme, and can be replaced by higher-precision differencing schemes such as central differencing. The backward differencing scheme can be defined as follows:

[0073] (9)

[0074] Where j represents the position of the j-th spatial step.

[0075] Discretize the continuity equations for each pipe section, i.e., the above-mentioned relation 4, to obtain the first part of the hydraulic solution equation, the continuity equation part. Similarly, discretize the momentum equation, i.e., the above-mentioned relation 4, to obtain the momentum equation part.

[0076] In addition to the two parts and boundary conditions mentioned above, this embodiment supplements the relationship of values ​​at pipe connections for the pipeline network. The process of determining hydraulic elements includes the following two parts: 1) Pressure equality: the pressure at each pipe connection node is equal; 2) Mass conservation: the total flow rate into each pipe connection node is equal to the total flow rate out of each pipe connection node. These two parts are collectively referred to as the nodal hydraulic equation part.

[0077] The boundary conditions section requires supplementary pressure or flow rate values ​​at the pipeline boundary points as the basis for calculation. At this point, it is essential to ensure that at least one pressure reference point exists throughout the entire pipeline network. Considering that the pressure power in Equation 5 is 1 while the mass flow rate power in the resistance term is 2 (i.e., the flow rate doubles and the pressure difference quadruples), the pipeline network is more sensitive to changes in pipeline flow rate. Furthermore, pressure values ​​within the pipeline network are generally relatively close; therefore, any deviation in pressure acquisition will result in a geometric increase in the pressure difference. For example, between two points with actual values ​​of 1 MPa and 0.98 MPa, a 1‰ acquisition error will cause the pressure difference to change from 0.02 MPa to 0.02198 MPa, an increase of approximately 10%, ultimately leading to a significant change in flow rate. Additionally, when fixing the pipeline insulation material, the heat dissipation of the pipeline is almost solely related to the internal and external temperatures, resulting in substantial deviations in subsequent temperature calculations. In summary, the hydraulic calculation section assumes that only one steam source node in a target area is assigned pressure, while the remaining nodes are assigned flow rate to ensure reliable results. The simulation boundary conditions section serves as the final part of the hydraulic equations.

[0078] In the initial stage, all parameters at each node in the hydraulic equations, except for pressure and mass flow rate, are referenced to the steam source point and considered as fixed values. Additionally, it is simply assumed initially that there is no condensate in any of the pipelines. These four parts together constitute a positive definite hydraulic equation set, which is calculated using sparse matrix techniques to obtain the pressure and mass flow rate values ​​at each node.

[0079] As can be seen from the above, this embodiment adopts a backward difference scheme to improve numerical stability and avoid divergence in the calculation process; it reasonably sets boundary conditions to reduce the impact of pressure acquisition error on flow calculation, effectively improving the accuracy of flow calculation; and it uses sparse matrix technology to reduce the computational complexity of the equation system, effectively improving the calculation speed and meeting the needs of rapid calculation for large-scale pipeline networks.

[0080] The above embodiments do not impose any limitations on how to determine the nodal enthalpy data of the pipeline network simulation model under the condition of satisfying energy balance. Based on the above embodiments, this application also provides a process for calculating the heat dissipation between each node of the pipeline based on the hydraulic element results, simultaneously establishing the energy equations of each pipeline, and iteratively calculating the enthalpy of each node through the finite difference method, which may include the following:

[0081] Based on the node pressure and flow distribution data of the current cycle, the heat dissipation between each node is determined. The pipeline energy equation is discretized using the finite difference method with backward difference as the difference format. Based on the fact that the inflow and outflow enthalpies of each node are the same and the downstream enthalpies of each node are the same, the corresponding node mixing relationship is determined at each node according to the physical connection relationship corresponding to the pipeline network simulation model. The node enthalpies of each node in the pipeline network simulation model are used as parameters to be determined, and the enthalpy of at least one steam source node is used as the boundary condition. Based on the node mixing relationship and the discretized pipeline energy equation, the node enthalpy data of the pipeline network simulation model are determined.

[0082] Pipeline heat loss data refers to the heat lost per unit length of pipeline to the environment, which can be calculated from the pipeline heat transfer coefficient and the temperature difference between steam and the environment, reflecting the pipeline's insulation effect and heat transfer characteristics. Nodal mixing relationships include the conservation of enthalpy at the inflow and outflow nodes (the total enthalpy at the inflow node equals the total enthalpy at the outflow node) and the equality of downstream enthalpy (the initial enthalpy of each pipe segment flowing out from the same node is the same). The energy equation describes the conservation of energy within the pipe segment, which simplifies in steady state to the relationship between enthalpy change along the pipe length and heat loss and latent heat of condensation. Thermal calculations are also based on three parts: nodal mixing relationships, discretization of the pipe segment energy equation, and boundary conditions. The boundary conditions specifically use the enthalpy of the steam source node (calculated using IAPWS-IF97 from its given pressure and temperature). Using mass flow rate, pressure, and heat loss as known inputs, a system of linear equations is established with nodal enthalpy as the unknown quantity to determine the enthalpy distribution of the entire network, and further, the temperature distribution can be calculated.

[0083] In this embodiment, since the calculation involves condensate volume and the temperature of wet steam and saturated dry steam at the same pressure is consistent, temperature is not used as the solution variable, especially the commonly used temperature of the homogeneous model is not used; instead, enthalpy is used as the solution variable. The thermodynamic equation calculation process also employs finite difference, discretized using a backward difference scheme. The energy equations for each pipe are the energy equation portion of the thermodynamic equation formed after discretizing the aforementioned relation 6. At the connection points between pipes, a nodal mixing relationship is adopted, meaning that the enthalpy of the upstream node is uniformly mixed and flows to the downstream pipe, thus forming two types of governing equations: 1) enthalpy conservation equation, where the inflow and outflow enthalpies are consistent; 2) downstream enthalpies are equal. These two parts together constitute the nodal mixing relationship. For example... Figure 3 As shown, the node mixing relationship for node A can be represented by the following formula: , ;in, This represents the mass flow rate at node A connected to pipe i, in kg / s. This represents the enthalpy at node A where pipe i is connected, in units of J / (kg·K), where N = 1, 2, 3, 4.

[0084] Because the flow mixing relationships at nodes and the downstream node parameters in pipeline calculations are entirely determined by upstream parameters and inherent parameters such as insulation layers, only the enthalpy of each steam source is needed as boundary conditions. According to IAPWS-IF97, enthalpy can be calculated from steam temperature and pressure. Since the pressure values ​​of non-pressure steam sources are not directly involved in the calculation, the calculated pressure may be higher than the actual pressure, leading to the presence of wet steam from non-pressure steam sources. Therefore, the smaller value between the calculated pressure and the collected pressure is preferred to avoid calculation instability caused by boundary parameters. The enthalpy assignment of each steam source constitutes the last part of the thermodynamic equation.

[0085] The above three equations constitute a positive definite equation. The mass flow rate is calculated using the results of hydraulic solutions. The equations can be calculated using sparse matrix techniques to obtain the enthalpy of each node.

[0086] As can be seen from the above, this embodiment can describe the phase transition process naturally and accurately by directly calculating the enthalpy, that is, the temperature remains constant while the enthalpy changes in the saturation region, thus achieving high-precision thermodynamic simulation. The combination of finite difference and nodal mixing relationship can ensure the rationality and stability of the calculation.

[0087] The above embodiments do not limit how to determine the amount of condensate. In this embodiment, after calculating the enthalpy at each point in the above process, and since some enthalpies are below the saturation enthalpy, the dryness fraction at each point is calculated. The difference in liquid water mass between two points is the amount of condensate between those two points, including the following:

[0088] Based on the node pressure distribution data of the current cycle, the saturated enthalpy of each node in the pipeline network simulation model is determined. Nodes whose enthalpy in the current cycle is lower than the corresponding saturated enthalpy at the current pressure are designated as target nodes for condensation phase change, and the pipe segments connecting these target nodes are designated as target pipe segments for condensation phase change. The enthalpy of each target node is updated to the corresponding saturated enthalpy at the current pressure to correct the enthalpy of each target node. The thermodynamic equations are discretized using the finite difference method. Based on the corrected enthalpy of each target node, the condensate volume of each target pipe segment is determined by the enthalpy at both ends of the target pipe segment according to the discretized thermodynamic equations. The condensate volume of each target pipe segment is treated as an independent mass term and updated to the pipeline network simulation model to serve as the condensate distribution and steam property parameters of each pipe segment in the next cycle of the pipeline network simulation model.

[0089] Among them, the target node (i.e., the condensate phase change node) refers to the node whose current enthalpy is lower than the saturation enthalpy at the corresponding pressure. This type of node involves a phase change process from steam to condensate. The target pipe section refers to the pipe section connecting the condensate phase change node, which is the physical carrier for the generation and separation of condensate. The saturated state refers to the equilibrium state in which steam and condensate coexist at a specific pressure, where the steam enthalpy is the saturation enthalpy corresponding to that pressure. The finite difference method is a numerical discretization method that solves by transforming continuous differential equations into discrete algebraic equations. This embodiment adopts the backward difference scheme, which has the advantages of strong numerical stability and no need for additional boundary condition processing.

[0090] In this embodiment, the node enthalpy is corrected to the saturated enthalpy, triggering and implementing the update of "steam physical parameters." Condensate volume is introduced into the model as a mass term, updating the condensate distribution. After obtaining the pressure and enthalpy of one iteration, the corresponding saturated enthalpy is first calculated based on the pressure of each node using the International Association for the Properties of Steam (IAPWS-IF97) formula. Then, the current calculated enthalpy of each node is compared with its saturated enthalpy, and all nodes with current enthalpy lower than their saturated enthalpy are marked as target nodes, and their connected pipe segments are the target pipe segments. Next, the enthalpy of all target nodes is updated (corrected) to the corresponding saturated enthalpy. Using the energy equation discretized by the finite difference method, based on the corrected upstream and downstream node enthalpies, the condensate volume generated by heat dissipation within the pipe segment is calculated. Finally, this calculated condensate volume is treated as an independent mass term removed from the steam mainstream and updated in the pipeline simulation model for the next round of hydraulic calculations.

[0091] Since the hydraulic calculations in S102 have determined the pressure values ​​at each node, the saturation temperature and saturation enthalpy of each node can be calculated based on these pressure values. In the thermal calculations, the heat of condensation of condensate has a significant impact; the heat of condensation of 0.01 kg of water vapor at 180℃ and 1 MPa is approximately enough to raise the temperature of 1 kg of water vapor by 7℃. Therefore, the enthalpy calculation results need post-processing to ensure that fluctuations in the condensate calculation process do not cause failures in subsequent calculations such as IAPWS-IF97. Because the condensate needs to be removed from the hydraulic equations, the remaining part involved in the calculation is entirely water vapor. Therefore, a preliminary enthalpy correction is performed, ensuring that the enthalpy at all locations where condensate exists is the saturation enthalpy. This correction avoids the abnormal situation where the enthalpy of the water vapor portion is lower than the saturation enthalpy. This correction process creates strong constraints on pressure, enthalpy, and condensate quantity at the end of the pipeline network where condensate exists, ensuring the stability of the condensate determination process. Based on the enthalpy after repair at each node, and according to the discretized calculation formula 6, the condensate water is treated as an unknown quantity, and the condensate water volume of the corresponding pipe section is calculated by using the enthalpy at both ends.

[0092] As can be seen from the above, this embodiment achieves accurate identification of condensate phase change nodes through saturated enthalpy forced correlation, ensuring the physical authenticity of condensate water volume calculation, ensuring that the calculation of condensate water volume originates from a reliable saturated state, avoiding numerical oscillations, and using the finite difference method for discretization to improve the accuracy of condensate water volume calculation. The condensate water volume is updated as an independent mass term, making the hydraulic-thermal calculation more consistent with actual working conditions and significantly improving the accuracy of pipeline parameter evaluation.

[0093] Based on the above embodiments, further, for each pipe with condensate flow, if there is a pipe section to be corrected where the enthalpy of both ends of the pipe is greater than or equal to the corresponding saturated enthalpy, then the condensate flow of each pipe section to be corrected is corrected to 0; the original calculation step size of the target pipe section with condensate flow greater than 0 is reduced to a preset step size, and the node parameters under the original calculation step size are mapped to the new grid node corresponding to the preset step size through linear interpolation, and the determination process of hydraulic elements and thermal parameters in the next round is carried out on the new grid node.

[0094] The section to be corrected refers to the section where the calculated condensate volume is obtained, but the enthalpy of both ends is greater than or equal to the corresponding saturated enthalpy. The condensate volume is caused by calculation errors. The preset step size is a refined calculation grid step size set for the condensate section, for example, 5m. Compared to a global calculation step size such as 20m, it can more accurately capture changes in end temperature and condensate volume. The original calculation step size can be the global calculation step size. Node parameters can include basic state parameters (such as pressure, enthalpy, and mass flow rate) and physical property parameters derived from the state parameters, such as temperature (calculated from pressure and enthalpy using the IAPWS-IF97 property library), density (calculated from pressure and enthalpy using the IAPWS-IF97 property library), viscosity, and other physical properties. Linear interpolation mapping is a data interpolation method that calculates the parameter values ​​of new grid nodes according to a linear relationship using the parameter values ​​of the original grid nodes, avoiding a complete re-iteration of the entire pipe network and reducing computational complexity.

[0095] After calculating the condensate volume for each pipe segment, a verification process is performed: For pipe segments with a calculated condensate volume greater than zero, if the enthalpy of both ends of the segment is greater than or equal to their respective saturated enthalpy, then the condensate volume is considered to be due to a calculation error and is corrected to zero. That is, if the enthalpy of both ends is above the saturated enthalpy, but the calculation results show the presence of condensate, the condensate volume for the segment is set to zero to prevent calculation errors from further affecting subsequent calculations. For target pipe segments where the condensate volume is indeed greater than zero, mesh adaptation is initiated: the calculation step size is reduced from the global calculation step size (e.g., 20 meters) to a preset fine step size (e.g., 5 meters). Parameters such as pressure, mass flow rate, and enthalpy on the original coarse mesh nodes are mapped to the newly generated fine mesh nodes using linear interpolation. Subsequent hydraulic and thermal calculations will be performed on this refined mesh.

[0096] In this embodiment, the generation of condensate water has a significant impact on the temperature and flow distribution inside the pipeline, especially in pipelines with low or even zero flow rates, where condensation is a key driver of mass flow throughout the pipeline. By using the occurrence of condensate water as a trigger condition, local mesh refinement is applied to specific pipe sections. Pipelines exhibiting condensation require smaller mesh calculations. For example, for low-flow or long-distance pipelines prone to condensation, the calculation mesh is automatically refined to improve the accuracy of end-point temperature and condensate quantity calculations. The temperature calculation results for a pipeline in this embodiment using step sizes of 20m, 10m, and 5m are shown below. Figure 4 The pressure calculation results are as follows Figure 5 As shown, the mass flow rate calculation results are as follows: Figure 6 As shown in Table 2, the heat loss and condensation amount in the pipeline are as follows. According to... Figures 4-6 It can be seen that the heat dissipation and condensate volume calculated by the three step sizes are basically consistent, proving the stability and effectiveness of the condensate calculation. Although the results under the three step sizes are basically consistent, there are differences in the patterns of temperature and pressure at the end. Using a smaller calculation step size in pipelines with longer condensate production will undoubtedly better reflect the actual situation where the end temperature gradually approaches the saturation temperature and the pressure continuously decreases. This achieves refined calculation modeling of the end thermal state and condensate volume, avoiding calculation errors. Especially in long-distance, low-flow pipelines, this error will seriously affect the condensate volume calculation. For the condensate calculation results, when condensate is identified in the corresponding pipeline, the calculation step size of the corresponding pipeline is reduced to the specified small step size value (5m). The original pipeline results are remapped to new nodes using linear interpolation, avoiding the need for a complete re-iteration of the entire pipeline network. The remaining pipelines are still iterated using the specified global step size. Subsequent hydraulic and thermal calculations are performed on the newly generated mesh. Compared with the complex surface flux interpolation calculation changes and possible complex modifications to misaligned meshes required by the finite volume method mesh, the computational complexity is greatly reduced.

[0097] Table 2 Summary of Pipeline Calculation Results

[0098]

[0099] As shown above, this embodiment uses the generation of condensate water as the basis for mesh refinement, targeting the pipelines that generate condensate water. This achieves refined simulation capabilities for critical pipelines, especially those with low flow rates at the end, providing a basis for assessing condensate volume in the pipeline network. Furthermore, compared to the complex mesh flux interpolation and misaligned meshes of the finite volume method, simple linear interpolation can complete the mapping of calculated values ​​between the old and new meshes, avoiding the need for a complete re-iteration of the entire pipeline network or complex finite volume method mesh flux interpolation calculations, thus significantly reducing the resource consumption of mesh refinement.

[0100] The above embodiments do not limit how to perform overall iterative control. Based on the above embodiments, the present invention also provides an exemplary implementation, which may include the following:

[0101] In consecutive calculation cycles, the pressure of all nodes, the mass flow rate of all pipe segments, the enthalpy of all nodes, and the condensate volume of all pipe segments in the current cycle of the pipeline network simulation model are obtained as the operating status parameters of the current cycle. If the changes in each operating status parameter of the current cycle and the adjacent previous cycle are all less than their respective preset convergence thresholds, then the hydraulic elements, thermal parameters, and condensate volume of the pipeline network simulation model in the current cycle are used as the operating status parameters of the steam pipeline network under the target operating conditions.

[0102] The operating status parameters can include the pressure of each node, the mass flow rate of each pipe section, the enthalpy of each node, and the condensate volume of each pipe section, comprehensively reflecting the operating status of the pipeline network. The preset convergence threshold can be a parameter change threshold set according to the engineering accuracy requirements, used to determine whether the model has reached dynamic equilibrium. For example, the pressure threshold is 1 Pa, the flow rate threshold is 0.01 kg / s, the enthalpy threshold is 50 J / kg, and the condensate volume threshold is 0.0001 kg / s.

[0103] In this embodiment, the overall iterative calculation of the pipeline network includes the above-mentioned hydraulic element determination process, thermal parameter determination process, and condensate quantity determination process. The hydraulic element determination results update the pressure and flow rates at each node. Then, thermal calculation updates the enthalpy at each node, and calculates parameters such as temperature, density, and viscosity based on pressure and enthalpy. Afterwards, condensate calculation re-verifies the condensate quantity of each pipe section based on the enthalpy of each node. The thermal parameters such as density at each node, as well as the condensate quantity of each pipe section, are then re-introduced into the hydraulic solution, and the hydraulic calculation equations are reconstructed, thus forming the overall iterative process. When the differences in pressure, mass flow rate, and enthalpy at each node, as well as the condensate quantity of each pipe section, are all less than preset iteration conditions such as a preset convergence threshold or the maximum number of iterations is reached after two iterations, the overall iteration is considered to have converged, the calculation is completed, and the results are processed and returned. During the iteration process, pressure and flow rate quickly stabilize. After the pressure stabilizes, the enthalpy at the end of the pipeline network gradually stabilizes along with the condensate quantity. Condensate is the main obstacle to convergence in iterative solutions, and the stability of its results plays a decisive role in the convergence of the entire calculation.

[0104] As can be seen from the above, this embodiment clearly defines the dynamic balance judgment criteria to ensure that the calculation results are stable and reliable; it avoids invalid iterations and, compared with the method of fixed number of iterations, can effectively improve the calculation efficiency, quickly respond to changes in operating conditions, and meet the needs of real-time industrial monitoring.

[0105] It should be noted that there is no strict order of execution for the steps in this application. As long as they conform to a logical order, these steps can be executed simultaneously or in a certain preset order. Figures 1-2This is just an illustrative example and does not mean that this is the only possible execution order.

[0106] This application also provides a corresponding apparatus for the steam pipeline network decoupling steady-state optimization method, further enhancing the practicality of the method. The apparatus can be described from both a functional module perspective and a hardware perspective. The steam pipeline network decoupling steady-state optimization apparatus provided in this application is described below. This apparatus is used to implement the steam pipeline network decoupling steady-state optimization method provided in this application. In this embodiment, the steam pipeline network decoupling steady-state optimization apparatus may include or be divided into one or more program modules. These one or more program modules are stored in a storage medium and executed by one or more processors to complete the steam pipeline network decoupling steady-state optimization method disclosed in Embodiment 1. The program module referred to in this embodiment refers to a series of computer program instruction segments capable of performing specific functions, which are more suitable than the program itself for describing the execution process of the steam pipeline network decoupling steady-state optimization apparatus in the storage medium. The following description will specifically introduce the functions of each program module in this embodiment. The steam pipeline network decoupling steady-state optimization apparatus described below can be referred to in correspondence with the steam pipeline network decoupling steady-state optimization method described above. From the perspective of functional modules, the steam pipeline network decoupling steady-state optimization apparatus provided in this embodiment may include:

[0107] The simulation model building module is used to determine the corresponding pipeline simulation model of the steam pipeline network based on the physical structure, pipeline parameters and target operating condition parameters of the steam pipeline network.

[0108] The hydraulic element calculation module is used to determine the nodal pressure distribution data and flow distribution data that meet the mass and momentum balance conditions based on the condensate distribution and steam property parameters of each pipe section in the pipeline network simulation model, so as to serve as hydraulic elements.

[0109] The thermal parameter calculation module is used to determine the nodal enthalpy data of the pipeline network simulation model under the condition of satisfying energy balance, based on hydraulic elements and pipeline heat loss data.

[0110] The condensate flow calculation module is used to determine the target node in the pipeline simulation model where condensation phase change occurs based on the node pressure distribution data and node enthalpy data. It associates the steam enthalpy of the target node with the saturation state under the current pressure, determines the condensate flow of each pipe section based on the saturation state, and updates the current condensate flow distribution and steam physical property parameters based on the condensate flow.

[0111] The result determination module is used to take the hydraulic elements, thermal parameters, and condensate volume of the pipeline network simulation model as the operating status parameters of the steam pipeline network under the target operating conditions.

[0112] For example, in some embodiments of this example, the result determination module can also be used to: determine the saturated enthalpy of each node in the pipeline network simulation model based on the node pressure distribution data of the current round; designate nodes whose enthalpy of the current round is lower than the corresponding saturated enthalpy at the current pressure as target nodes for condensation phase change, and designate the pipe segments connecting the target nodes as target pipe segments for condensation phase change; update the enthalpy of each target node to the corresponding saturated enthalpy at the current pressure to correct the enthalpy of each target node; discretize the thermodynamic equation using the finite difference method, and based on the corrected enthalpy of each target node, determine the condensate volume of the corresponding target pipe segment through the enthalpy at both ends of each target pipe segment according to the discretized thermodynamic equation; update the condensate volume of each target pipe segment as an independent mass term to the pipeline network simulation model, so as to serve as the condensate distribution and steam property parameters of each pipe segment in the next round of the pipeline network simulation model.

[0113] As an exemplary implementation of the above embodiments, the result determination module can be further used to: for each pipe with condensate volume, if there is a pipe section to be corrected where the enthalpy of both ends of the pipe section is greater than or equal to the corresponding saturated enthalpy, then the condensate volume of each pipe section to be corrected is corrected to 0; the original calculation step size of the target pipe section with condensate volume greater than 0 is reduced to a preset step size, and the node parameters under the original calculation step size are mapped to the new grid node corresponding to the preset step size through linear interpolation, and the determination process of hydraulic elements and thermal parameters in the next round is performed on the new grid node.

[0114] For example, in some other embodiments of this embodiment, the result determination module can also be used to: in consecutive calculation rounds, obtain the pressure of all nodes, the mass flow rate of all pipe segments, the enthalpy of all nodes, and the condensate volume of all pipe segments of the pipeline network simulation model in the current round as the operating status parameters of the current round; if the change in each operating status parameter of the current round and the adjacent previous round is less than their respective preset convergence thresholds, then the hydraulic elements, thermal parameters, and condensate volume of the pipeline network simulation model in the current round are used as the operating status parameters of the steam pipeline network under the target operating conditions.

[0115] For example, in some other embodiments of this example, the simulation model construction module described above can also be used to: construct a topology model of the steam pipeline network by taking the transmission channels of the steam pipeline network as pipelines and the physical equipment at both ends of the transmission channels as nodes, based on the physical structure of the steam pipeline network; configure corresponding physical attribute parameters for each pipeline in the topology model according to the pipeline parameters of the steam pipeline network, and configure corresponding operating boundary conditions for the boundary nodes according to the operating condition parameters; the operating boundary conditions include the pressure and temperature of the source nodes and the mass flow rate of the sink nodes; and determine the target area containing the superheated steam source in the topology model according to the operating boundary conditions, and discretize the pipelines in each target area according to a preset length to generate a digital simulation model.

[0116] For example, in some other embodiments of this example, the hydraulic element calculation module described above can also be used to: determine the mass flow conservation condition at the nodes based on the physical connection relationship corresponding to the pipeline network simulation model, and based on the fact that the pressure at the locations of the nodes connected to each pipe segment is the same, and the total inflow and outflow of the nodes connected to each pipe segment are the same; discretize the pipeline continuity equation and momentum equation respectively using the finite difference method, and the difference format adopts backward difference; based on the fact that the steam density of each node in the pipeline network simulation model is constant in one round of iterative calculation, and the boundary condition is that each target area of ​​the pipeline network simulation model has only one steam source node configured with pressure parameters and the remaining nodes configured with mass flow parameters, and based on the mass flow conservation condition, the discretized pipeline continuity equation and the discretized momentum equation, determine the node pressure distribution data and flow distribution data of the pipeline network simulation model in the current round.

[0117] For example, in some other embodiments of this example, the above-mentioned thermal parameter calculation module can also be used to: determine the heat dissipation between nodes based on the node pressure distribution data and flow distribution data of the current cycle; discretize the pipeline energy equation using the finite difference method, with the difference format being backward difference; determine the corresponding node mixing relationship at each node based on the physical connection relationship corresponding to the pipeline network simulation model, according to the fact that the inflow and outflow enthalpies of each node are the same and the downstream enthalpies of each node are the same; take the node enthalpies of each node in the pipeline network simulation model as parameters to be determined, take the enthalpy of at least one steam source node as boundary conditions, and determine the node enthalpy data of the pipeline network simulation model according to the node mixing relationship and the discretized pipeline energy equation.

[0118] The request task processing device mentioned above is described from the perspective of functional modules. Furthermore, the present invention also provides an electronic device, which is described from the perspective of hardware. Figure 7This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present invention. The electronic device includes a memory 701 and a processor 702. The memory 701 stores a computer program, and the processor 702 is configured to run the computer program to perform the steps in any of the above-described requests task processing method embodiments.

[0119] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above-described requests task processing method embodiments when it runs.

[0120] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0121] Embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above-described requests task processing method embodiments.

[0122] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps in any of the above-described requests task processing method embodiments.

[0123] The foregoing has provided a detailed description of the steam pipeline network decoupling steady-state optimization method, electronic device, computer-readable storage medium, and computer program product provided by this invention. The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Whether the units and algorithm steps of the various examples described in the disclosed embodiments are executed in electronic hardware or computer software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, and such implementations should not be considered beyond the scope of this invention. Several improvements and modifications can be made to this invention without departing from the principles of this invention, and these improvements and modifications also fall within the protection scope of this invention.

Claims

1. A decoupled steady-state optimization method for steam pipeline networks, characterized in that, include: Based on the physical structure, pipeline parameters, and target operating condition parameters of the steam pipeline network, determine the corresponding pipeline network simulation model; Based on the condensate distribution and steam properties of each pipe section in the pipeline network simulation model, determine the nodal pressure distribution data and flow distribution data when the mass and momentum balance conditions are met, as hydraulic elements. Based on the hydraulic elements and pipeline heat loss data, determine the nodal enthalpy data of the pipeline network simulation model under the condition of satisfying energy balance; Based on the node pressure distribution data and the node enthalpy data, the target node in the pipeline simulation model that undergoes condensation phase change is determined, the steam enthalpy of the target node is associated with the saturation state under the current pressure, the condensate volume of each pipe section is determined based on the saturation state, and the current condensate distribution and steam physical property parameters are updated based on the condensate volume. The hydraulic elements, thermal parameters, and condensate volume of the pipeline network simulation model under dynamic equilibrium are used as the operating status parameters of the steam pipeline network under the target operating conditions.

2. The decoupling steady-state optimization method for steam pipeline networks according to claim 1, characterized in that, Based on the node pressure distribution data and the node enthalpy data, the target node in the pipeline simulation model where condensation phase change occurs is determined. The steam enthalpy of the target node is correlated with the saturation state at the current pressure. Based on the saturation state, the condensate flow rate of each pipe section is determined, including: Based on the node pressure distribution data of the current round, determine the saturated enthalpy of each node in the pipeline network simulation model; The node whose enthalpy of the current cycle is lower than the corresponding saturated enthalpy at the current pressure is taken as the target node for condensation phase change, and the pipe segment connected to the target node is taken as the target pipe segment for condensation phase change. The enthalpy of each target node is updated to the corresponding saturated enthalpy under the current pressure to correct the enthalpy of each target node; The thermodynamic equation is discretized using the finite difference method. Based on the corrected enthalpy of each target node, the condensate volume of each target pipe section is determined by the enthalpy of the two ends of each target pipe section according to the discretized thermodynamic equation. The condensate volume of each target pipe segment is treated as an independent mass item and updated to the pipeline network simulation model, so as to serve as the condensate distribution and steam property parameters of each pipe segment in the pipeline network simulation model in the next round.

3. The steam pipeline network decoupling steady-state optimization method according to claim 2, characterized in that, The condensate volume of each pipe section is determined based on the saturation state, including: For each pipe section with condensate flow, if there is a pipe section to be corrected where the enthalpy of both ends is greater than or equal to the corresponding saturated enthalpy, then the condensate flow of each pipe section to be corrected will be corrected to 0. The original calculation step size of the target pipe section with a condensate volume greater than 0 is reduced to a preset step size, and the node parameters of the original calculation step size are mapped to the new grid node corresponding to the preset step size through linear interpolation. The determination process of hydraulic and thermal parameters in the next round is carried out on the new grid node.

4. The decoupling steady-state optimization method for steam pipeline networks according to claim 1, characterized in that, The hydraulic elements, thermal parameters, and condensate flow rate of the pipeline network simulation model under dynamic equilibrium conditions include: In consecutive calculation cycles, the pressure of all nodes, the mass flow rate of all pipe segments, the enthalpy of all nodes, and the condensate volume of all pipe segments of the pipeline network simulation model in the current cycle are obtained as the operating status parameters of the current cycle. If the changes in each operating state parameter of the current cycle and the adjacent previous cycle are all less than their respective preset convergence thresholds, then the hydraulic elements, thermal parameters and condensate volume of the pipeline network simulation model in the current cycle are taken as the operating state parameters of the steam pipeline network under the target operating conditions.

5. The decoupling steady-state optimization method for steam pipeline networks according to claim 1, characterized in that, Based on the physical structure, pipeline parameters, and target operating condition parameters of the steam pipeline network, a pipeline simulation model corresponding to the steam pipeline network is determined, including: Based on the physical structure of the steam pipeline network, the transmission channels of the steam pipeline network are taken as pipes and the physical equipment at both ends of the transmission channels are taken as nodes, and the corresponding topology model of the steam pipeline network is constructed. Based on the pipeline parameters of the steam pipeline network, corresponding physical property parameters are configured for each pipeline in the topology model, and corresponding operating boundary conditions are configured for the boundary nodes based on the target operating condition parameters; the operating boundary conditions include the pressure and temperature of the source node and the mass flow rate of the sink node. Based on the operational boundary conditions, the target area containing the superheated steam source is determined in the topology model, and the pipelines in each target area are discretized according to a preset length to generate a pipeline network simulation model.

6. The steam pipeline network decoupling steady-state optimization method according to any one of claims 1 to 5, characterized in that, Based on the condensate distribution and steam properties of each pipe section in the pipeline network simulation model, determine the nodal pressure distribution and flow rate distribution data that satisfy the mass and momentum balance conditions, including: Based on the physical connection relationship corresponding to the pipeline network simulation model, and considering that the pressure at the locations of the nodes connected to each pipe segment is the same, and that the total inflow and outflow of the nodes connected to each pipe segment are the same, the mass flow conservation condition at the nodes is determined. The finite difference method, with backward difference as the finite difference scheme, is used to discretize the pipeline continuity equation and momentum equation respectively. Based on the fact that the steam density of each node in the pipeline simulation model is constant during one round of iterative calculation, the boundary conditions are set so that each target region of the pipeline simulation model has only one steam source node configured with pressure parameters and the remaining nodes configured with mass flow rate parameters. Based on the mass flow rate conservation condition, the discretized pipeline continuity equation and the discretized momentum equation, the node pressure distribution data and flow rate distribution data of the pipeline simulation model in the current round are determined.

7. The decoupling steady-state optimization method for steam pipeline networks according to any one of claims 1 to 5, characterized in that, Based on the hydraulic parameters and pipeline heat loss data, determine the nodal enthalpy data of the pipeline network simulation model under the condition of satisfying energy balance, including: Based on the node pressure distribution data and flow distribution data of the current round, determine the heat dissipation between each node; The pipeline energy equation is discretized using the finite difference method, with backward difference as the finite difference scheme. Based on the fact that the inflow and outflow enthalpies of each node are the same and the downstream enthalpies of each node are the same, the corresponding node mixing relationship is determined at each node based on the physical connection relationship corresponding to the pipeline network simulation model. The enthalpy of each node in the pipeline simulation model is taken as a parameter to be determined, and the enthalpy of at least one steam source node is taken as a boundary condition. Based on the mixing relationship of each node and the discretized pipeline energy equation, the node enthalpy data of the pipeline simulation model are determined.

8. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the steam network decoupling steady-state optimization method as described in any one of claims 1 to 7 when executing the computer program.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the steam pipeline network decoupling steady-state optimization method as described in any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the steam pipeline decoupling steady-state optimization method according to any one of claims 1 to 7.

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