Steam pipe network condensate water distribution prediction method, device, equipment and medium

Abstract

The invention discloses a steam pipe network condensate water distribution prediction method, device and equipment and a medium, and relates to the technical field of smart city operation, and the method comprises the steps: building a condensate water distribution prediction model; the condensate water distribution prediction model comprises a heat escape condensation amount calculation model and an instantaneous condensation amount calculation model; inputting the gas source parameter, the pipeline parameter and the steam state parameter of each node of the pipe network into a condensate water distribution prediction model; the heat escape condensation amount is calculated through the heat escape condensation amount calculation model, and the instantaneous condensation amount is calculated through the instantaneous condensation amount calculation model; and outputting a condensate water distribution prediction result according to the sum of the heat escape condensation amount and the instantaneous condensation amount. According to the method, second-level real-time calculation can be achieved, pipe network condensate water distribution can be rapidly and accurately predicted, the average error is reduced, cost is low, adaptability is high, and data support is provided for steam pipe network operation optimization.

Description

Technical Field

[0001] The present invention relates to the technical field of smart city operation, and particularly to a method, device, equipment and medium for predicting the condensate distribution in a steam pipe network. Background Art

[0002] As an important heat energy transmission system in industrial production, the operation efficiency of a steam pipe network directly affects the energy utilization rate and production cost. During the steam transmission process, due to heat loss and pressure changes, steam continuously condenses to generate condensate. The accumulation of condensate can cause problems such as water hammer, pipeline corrosion, and equipment damage, seriously affecting the safe operation and thermal efficiency of the pipe network.

[0003] In related technical solutions, the steam pipe network system generally lacks effective means for predicting condensate distribution, mainly relying on empirical judgment or regular manual drainage, resulting in the inability to timely grasp the condensate generation situation in each section of the pipe network. At the same time, the parameter coupling effect is often ignored, leading to large prediction errors. Eventually, either excessive drainage of condensate causes steam waste, or insufficient drainage of condensate causes potential safety hazards.

[0004] Therefore, how to accurately predict the condensate distribution in a steam pipe network is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] The purpose of the present invention is to provide a method, device, equipment and medium for predicting the condensate distribution in a steam pipe network, which can quickly and accurately predict the condensate distribution in the pipe network in real time, with low cost and strong adaptability, and provide data support for the operation optimization of the steam pipe network.

[0006] To solve the above technical problem, the present invention provides a method for predicting the condensate distribution in a steam pipe network, including: Establishing a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate amount calculation model and an instantaneous condensate amount calculation model; Inputting the gas source parameters, pipeline parameters, and steam state parameters of each node in the pipe network into the condensate distribution prediction model; Calculating the heat escape condensate amount by using the heat escape condensate amount calculation model, and calculating the instantaneous condensate amount by using the instantaneous condensate amount calculation model; Outputting a condensate distribution prediction result according to the sum of the heat escape condensate amount and the instantaneous condensate amount.

[0007] In the first aspect, in the above method for predicting the condensate distribution in a steam pipe network provided by the present invention, calculating the heat escape condensate amount includes: Calculating the heat loss per unit pipe length with insulation parameters; Calculating the heat escape condensate amount according to the latent heat of phase change, the pipeline length, and the heat loss per unit pipe length with insulation parameters.

[0008] On the other hand, in the above-mentioned steam pipe network condensate distribution prediction method provided by the present invention, calculating the heat loss per unit pipe length including heat preservation parameters includes: Calculating the heat loss per unit pipe length including heat preservation parameters according to the steam temperature, ambient temperature, heat conductivity coefficient of the heat preservation material, outer diameter of the pipe, outer diameter of the heat preservation layer, and ambient convection coefficient.

[0009] On the other hand, in the above-mentioned steam pipe network condensate distribution prediction method provided by the present invention, calculating the instantaneous condensation amount includes: Calculating the two-phase pressure drop and the flow pressure drop, and obtaining the total pressure drop according to the sum of the two-phase pressure drop and the flow pressure drop; Calculating the instantaneous condensation amount according to the total pressure drop, the change value of steam dryness, the steam mass, the pipeline input pressure, and the condensation gain factor.

[0010] On the other hand, in the above-mentioned steam pipe network condensate distribution prediction method provided by the present invention, calculating the two-phase pressure drop includes: Calculating the friction coefficient; Calculating the pipeline elevation difference according to the pipeline length and the pipeline inclination angle; Calculating the two-phase pressure drop according to the friction coefficient, the pipeline elevation difference, the pipeline length, the outer diameter of the pipe, the fluid density, and the average flow velocity of the fluid.

[0011] On the other hand, in the above-mentioned steam pipe network condensate distribution prediction method provided by the present invention, calculating the friction coefficient includes: Calculating the Re number according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipe, and the dynamic viscosity of the fluid; Calculating the friction coefficient through an implicit equation according to the Re number, the outer diameter of the pipe, and the pipe roughness; While calculating the friction coefficient, using the Newton iteration method to gradually approximate the root of the implicit equation locally linearly, and updating the friction coefficient in each iteration.

[0012] On the other hand, in the above-mentioned steam pipe network condensate distribution prediction method provided by the present invention, calculating the friction coefficient includes: Calculating the Re number according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipe, and the dynamic viscosity of the fluid; Calculating a first intermediate variable according to the Re number and the pipe roughness; and calculating a second intermediate variable according to the Re number; Calculating the friction coefficient through an explicit equation according to the Re number, the first intermediate variable, and the second intermediate variable.

[0013] To solve the above technical problems, the present invention also provides a steam pipe network condensate distribution prediction device, including: A model establishment module for establishing a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate amount calculation model and an instantaneous condensate amount calculation model; A data input module for inputting the basic network data including gas source parameters and pipeline parameters, as well as the steam state parameters of each node of the network into the condensate distribution prediction model; A condensate amount calculation module for calculating the heat escape condensate amount using the heat escape condensate amount calculation model and calculating the instantaneous condensate amount using the instantaneous condensate amount calculation model; A result output module for outputting a condensate distribution prediction result according to the sum of the heat escape condensate amount and the instantaneous condensate amount.

[0014] To solve the above technical problems, the present invention also provides an electronic device, including: A memory for storing a computer program; A processor for implementing the steps of the above-mentioned steam network condensate distribution prediction method when executing the computer program.

[0015] To solve the above technical problems, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned steam network condensate distribution prediction method are implemented.

[0016] As can be seen from the above technical solutions, the steam network condensate distribution prediction method provided by the present invention includes: establishing a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate amount calculation model and an instantaneous condensate amount calculation model; inputting the gas source parameters, pipeline parameters, and steam state parameters of each node of the network into the condensate distribution prediction model; calculating the heat escape condensate amount using the heat escape condensate amount calculation model and calculating the instantaneous condensate amount using the instantaneous condensate amount calculation model; outputting a condensate distribution prediction result according to the sum of the heat escape condensate amount and the instantaneous condensate amount.

[0017] The beneficial effect of the present invention is that the above-mentioned steam network condensate distribution prediction method provided by the present invention considers various condensation mechanisms, establishes a condensate distribution prediction model between the gas source parameters, pipeline parameters, steam state parameters and the condensate generation amount, calculates the heat escape condensate amount using the heat escape condensate amount calculation model and calculates the instantaneous condensate amount using the instantaneous condensate amount calculation model. According to the sum of the heat escape condensate amount and the instantaneous condensate amount, it can achieve second-level real-time calculation, quickly and accurately predict the condensate distribution of the network, reduce the average error, have low cost and strong adaptability, and provide data support for the operation optimization of the steam network.

[0018] In addition, the present invention also provides a corresponding steam pipe network condensate distribution prediction device, an electronic device, and a computer-readable storage medium for the steam pipe network condensate distribution prediction method, which have the same or corresponding technical features as the steam pipe network condensate distribution prediction method mentioned above, and the effects are the same as above. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] To more clearly illustrate the embodiments of the present invention, the accompanying drawings required for use in the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.

[0020] Figure 1 is a flowchart of the steam pipe network condensate distribution prediction method provided by the embodiments of the present invention; Figure 2 is a schematic structural diagram of the steam pipe network condensate distribution prediction device provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the protection scope of the present invention.

[0022] It should be noted that in the description of the present invention, the terms "include", "comprise" or any other variation thereof are intended to cover a non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. The terms "first", "second", etc. in the present invention are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0023] To enable those skilled in the art of the present technology to better understand the solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] Combined with the specific application environment architecture or specific hardware architecture on which the execution of the steam pipe network condensate distribution prediction method depends, the specific application environment architecture or specific hardware architecture is described herein.

[0025] Embodiments of the present invention provide a steam pipe network condensate distribution prediction method, and the method will be described in detail in combination with the execution process of the steam pipe network condensate distribution prediction method.Figure 1 The flowchart of the condensate distribution prediction method provided by the embodiment of the present invention is as follows. As Figure 1 shown, the method includes: S101. Establish a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate calculation model and an instantaneous condensate calculation model.

[0026] It should be noted that the condensate distribution prediction model established by the present invention is a model for predicting the condensate distribution in the steam pipe network. In the condensate distribution prediction model, the heat escape condensate calculation and the instantaneous condensate are core calculation items in parallel. The condensate distribution prediction model can be composed of a heat escape condensate calculation model and an instantaneous condensate calculation model. Among them, the heat escape condensate refers to the amount of condensate generated due to heat dissipation from the pipe wall; the heat escape condensate calculation model is a model for quantifying the amount of condensate generated due to heat dissipation from the pipe wall. The instantaneous condensate refers to the amount of condensate generated during the pressure change process (especially during a sudden drop); the instantaneous condensate calculation model is a model for quantifying the amount of condensate generated during the pressure change process (especially during a sudden drop).

[0027] S102. Input the gas source parameters, pipeline parameters, and steam state parameters of each node in the pipe network into the condensate distribution prediction model.

[0028] It should be noted that in the present invention, the gas source parameters refer to a series of quantified indicators of the physical, chemical, and thermodynamic properties of the gas source in the steam pipe network. The gas source parameters can include the latent heat of phase change (i.e., the total heat absorbed / released during the phase change of a substance), ambient temperature, ambient convection coefficient, fluid density, average fluid velocity, fluid dynamic viscosity, etc. The pipeline parameters refer to a series of quantified indicators describing the physical characteristics, geometric dimensions, operating status, and transportation capacity of the steam pipeline. The pipeline parameters can include pipeline length, pipeline outer diameter, pipeline inclination angle, insulation layer outer diameter, thermal conductivity of the insulation material, etc. The steam state parameters of each node in the pipe network refer to the quantified indicators of the physical state of the steam at each node in the steam pipe network. The steam state parameters of each node in the pipe network can include steam temperature, steam mass, steam dryness change value, etc.

[0029] S103. Calculate the heat escape condensate using the heat escape condensate calculation model, and calculate the instantaneous condensate using the instantaneous condensate calculation model.

[0030] In implementation, the heat escape condensate can be calculated in real time using the heat escape condensate calculation model and the instantaneous condensate can be calculated in real time using the instantaneous condensate calculation model .

[0031] S104. Output the condensate distribution prediction result according to the sum of the heat escape condensate and the instantaneous condensate.

[0032] In implementation, the condensate distribution prediction result can be 。

[0033] In the above condensate distribution prediction method for steam pipe networks provided by the embodiments of the present invention, various condensation mechanisms are considered, a condensate distribution prediction model is established between gas source parameters, pipeline parameters, steam state parameters and the amount of condensate generated, the heat escape condensate amount is calculated using the heat escape condensate amount calculation model, and the instantaneous condensate amount is calculated using the instantaneous condensate amount calculation model. According to the sum of the heat escape condensate amount and the instantaneous condensate amount, real-time calculation at the second level can be achieved, the condensate distribution in the pipe network can be predicted quickly and accurately, the average error can be reduced, the cost is low, and the adaptability is strong, providing data support for the operation optimization of the steam pipe network.

[0034] In practical applications, before performing step S103, the compliance of the pipe network topology can be verified, including isolated nodes, pipe materials, connectivity, etc. Specifically, the connectivity of pipe segments can be checked (no isolated nodes). The connectivity of pipe segments requires that all pipe segments in the pipeline system should be correctly connected to form a complete network without disconnection or non-connectivity. A node is the connection point of a pipe segment, and an isolated node refers to a node that is not connected to other pipe segments. Such isolated points cannot exist in a steam pipe, otherwise it will affect the function of the entire system. Through verification, it is ensured that the pipeline system meets the design requirements in terms of structure, providing an accurate basis for subsequent fluid flow analysis, pressure calculation, etc. In addition, material parameter matching can also be performed. For example, a hydrophobic cotton database can be established to obtain the change of the thermal conductivity of hydrophobic cotton under different temperature conditions and present it in the form of a curve, which helps to understand the change of the heat insulation performance of hydrophobic cotton under different working condition temperatures and provides a basis for the reasonable selection of hydrophobic cotton; using a computer program or related algorithms, based on the basic information such as the pipe diameter input, the recommended value of the insulation layer thickness corresponding to it can be quickly and accurately found, improving work efficiency and accuracy.

[0035] After performing step S104, a condensate distribution prediction report can be generated according to the condensate distribution prediction result, including the condensate amount of each pipe segment, the recommended hydrophobic strategy, etc., realizing a closed-loop from prediction to application.

[0036] Furthermore, in specific implementation, in the above condensate distribution prediction method for steam pipe networks provided by the embodiments of the present invention, step S103 calculates the heat escape condensate amount, which specifically may include: calculating the heat loss per unit pipe length with insulation parameters; calculating the heat escape condensate amount according to the latent heat of phase change, the pipe length, and the heat loss per unit pipe length with insulation parameters.

[0037] In implementation, during the process of calculating the heat escape condensate amount using the heat escape condensate amount calculation model, the heat loss per unit pipe length with insulation parameters can be calculated first, and then according to the latent heat of phase change, the pipe length, and the heat loss per unit pipe length with insulation parameters, the heat escape condensate amount can be calculated using the following formula (1): ; (1) Wherein, represents the heat escape condensation amount, which refers to the mass of the substance transformed from gaseous state to liquid state per hour, and the unit is usually kilograms per hour (kg / h); represents the heat loss per unit pipe length with insulation parameters; represents the pipe length, that is, the actual length of the pipe through which the fluid flows; represents the latent heat of phase change, which refers to the heat absorbed / released during the phase change process of the substance ( ), and can be obtained by referring to the superheated steam table.

[0038] Furthermore, in specific implementation, in the above steps, calculating the heat loss per unit pipe length with insulation parameters may specifically include: calculating the heat loss per unit pipe length with insulation parameters according to the steam temperature, ambient temperature, thermal conductivity of the insulation material, outer diameter of the pipe, outer diameter of the insulation layer, and ambient convection coefficient.

[0039] In implementation, based on the heat transfer principle of the cylindrical wall, according to the steam temperature, ambient temperature, thermal conductivity of the insulation material, outer diameter of the pipe, outer diameter of the insulation layer, and ambient convection coefficient, the following formula (2) can be used to calculate the heat loss per unit pipe length with insulation parameters: ; (2) Wherein, represents the steam temperature (°C), represents the ambient temperature (°C), represents the thermal conductivity of the hydrophobic cotton (W / m·K), and the reference value is 0.035 - 0.045; represents the outer diameter of the pipe (m); represents the outer diameter of the insulation layer (m), where is the thickness of the insulation layer; represents the ambient convection coefficient (W / m²·K), and the value is 5 - 25 (depending on the wind speed).

[0040] It should be noted that the above formula (1) combined with formula (2) can be used as a heat escape condensation amount calculation model.

[0041] The present invention can use the energy conservation equation to verify , and the energy conservation direction can be the following formula (3): ; (3) Wherein, , respectively represent the specific enthalpy of the fluid at the inlet and outlet of the pipe, with the unit of joules per kilogram (J / kg). The specific enthalpy is the enthalpy of the working fluid per unit mass and is a thermodynamic state parameter, reflecting the energy state of the fluid; , are the flow velocities of the fluid at the inlet and outlet of the pipeline respectively, with the unit of meters per second (m / s), reflecting the flow speed of the fluid at different positions; , are the position heights of the fluid at the inlet and outlet of the pipeline respectively, with the unit of meters, used to determine the position of the fluid in the vertical direction; is the potential energy term, reflecting the change in pipeline height ( represents the acceleration due to gravity, is the node elevation); is the mass flow rate (kg / s).

[0042] Furthermore, in specific implementation, in the above-mentioned steam pipe network condensate distribution prediction method provided by the embodiments of the present invention, in step S103 of calculating the instantaneous condensation amount, it may specifically include: calculating the two-phase pressure drop and the flow pressure drop, and obtaining the total pressure drop according to the sum of the two-phase pressure drop and the flow pressure drop; calculating the instantaneous condensation amount according to the total pressure drop, the steam dryness change value, the steam mass, the pipeline input pressure, and the condensation gain factor.

[0043] In implementation, during the process of calculating the instantaneous condensation amount using the instantaneous condensation amount calculation model, the two-phase pressure drop and the flow pressure drop can be calculated first. The two-phase pressure drop is specific to the two-phase flow system and includes the frictional pressure drop as a component; the flow pressure drop refers to the total pressure drop (including frictional, gravitational, acceleration, and form drag components) during the fluid motion, where represents the density of the fluid, represents the acceleration due to gravity; represents the pipeline elevation difference. The flow pressure drop is based on the principle of hydrostatics and reflects that the flow pressure drop is proportional to the fluid density, the acceleration due to gravity, and the pipeline elevation difference at both ends, and is related to the inclination angle; for example, in a vertical pipeline for transporting liquid, the greater the liquid density and the greater the pipeline height difference, the greater the flow pressure drop. Then, according to the sum of the two-phase pressure drop and the flow pressure drop , the total pressure drop is obtained. That is, the total pressure drop is composed of two parts: the two-phase pressure drop and the flow pressure drop, referring to the total difference in pressure between two points along the flow direction when the fluid flows in the pipeline, reflecting the total pressure loss caused by the fluid overcoming the pipeline resistance and the change in potential energy, etc.

[0044] Then, according to the total pressure drop , the steam dryness change value, the steam mass, the pipeline input pressure, and the condensation gain factor, the instantaneous condensation amount can be calculated using the following formula (4): ; (4) where, Represents the instantaneous condensation amount, which refers to the mass of the substance that changes from gaseous to liquid during the instantaneous condensation process; Represents the steam mass, that is, the mass of the steam participating in the instantaneous condensation process, with the unit of kilogram (kg); 、 Represent the dryness of the steam at the inlet and outlet of the process respectively; Dryness is a parameter that measures the proportion of steam mass in wet steam, with a value range of 0 - 1, where 0 means all liquid and 1 means all gas; Is the change in steam dryness; Represents the condensation gain factor, which is a correction factor based on the Re number (i.e., Reynolds number) or the inclination angle, without a fixed unit; Represents the input pressure, with the unit of Pascal (Pa) or megapascal (MPa).

[0045] It should be noted that the above instantaneous condensation amount can include the inclination angle correction, indicating that the calculation of this condensation amount takes into account the influence of the inclination angle factor. This formula (4) is established based on the relevant theories or experiences considering the influence of the inclination angle. Some parameters in the formula (such as etc.) may be determined or corrected by considering the effect of the inclination angle on the system (such as the component of gravity along the inclined direction affecting fluid flow, energy exchange, etc.), so that the calculated can more accurately reflect the instantaneous condensation amount in the case with an inclination angle.

[0046] It should be noted that when the pipeline inclination angle is less than or equal to the set angle (such as 10°), the can be directly used for the instantaneous condensation amount; When the pipeline inclination angle is greater than the set angle (such as 10°), the condensation gain factor of the inclined section is activated, and specifically, the following formula (5) can be used for calculation: ; (5) Among them, Represents the condensation gain factor of the inclined section. It is obtained by correcting the basic coefficient (a coefficient related to the system characteristics) according to the pipeline inclination angle . Formula (5) shows that the larger the inclination angle , the more relatively increases, reflecting the enhancing effect of the inclination angle on instantaneous condensation. When there is a large inclination angle in the pipeline (such as ), the calculation of the instantaneous condensation amount is corrected. In the calculation of the instantaneous condensation amount, can be introduced to replace the original coefficient , so as to more accurately consider the influence of the inclination angle on the instantaneous condensation process, enable the calculation results to better reflect the instantaneous condensation situation under actual working conditions, and improve the accuracy of relevant engineering calculations and analyses.

[0047] Furthermore, in specific implementation, in the above steps, calculating the two-phase pressure drop includes: calculating the friction coefficient; calculating the pipeline elevation difference according to the pipeline length and the pipeline inclination angle; calculating the two-phase pressure drop according to the friction coefficient, the pipeline elevation difference, the pipeline length, the pipeline outer diameter, the fluid density, and the average flow velocity of the fluid.

[0048] In implementation, during the process of calculating the two-phase pressure drop, the friction coefficient can be calculated first; then, the following formula (6) can be used to calculate the pipeline elevation difference according to the pipeline length and the pipeline inclination angle: ; (6) where represents the pipeline elevation difference; represents the pipeline inclination angle, which refers to the angle formed by the pipeline center line and the horizontal direction.

[0049] After that, according to the friction coefficient, the pipeline elevation difference, the pipeline length, the pipeline outer diameter, the fluid density, and the average flow velocity of the fluid, the following formula (7) can be used to calculate the two-phase pressure drop: ; (7) where represents the two-phase pressure drop; represents the friction coefficient, which is related to factors such as the inner wall roughness of the pipeline and the fluid flow state (laminar flow or turbulent flow), and reflects the magnitude of the frictional resistance between the fluid and the pipeline wall; represents the density of the fluid, which is the mass per unit volume of the fluid; represents the average flow velocity of the fluid, that is, the average speed of the fluid flowing in the pipeline; represents the acceleration due to gravity; represents the pipeline elevation difference, which refers to the height difference between the two ends of the pipeline in the vertical direction and is used to measure the position difference of the pipeline in the vertical direction.

[0050] It should be noted that the present invention considers that when the pipeline is inclined, in addition to the frictional resistance with the pipe wall, the fluid is also affected by the component force of gravity along the pipeline direction. Therefore, this term is added to correct the additional influence of the gravity effect on the pressure drop caused by the pipeline inclination, so that the equation can more accurately calculate the frictional pressure drop of the fluid in the inclined pipeline.

[0051] When fluid flows in a pipeline, the friction coefficient is an important parameter to measure the friction resistance characteristics between the fluid and the pipe wall, and plays a key role in calculating pressure drop, flow rate, etc. In specific implementation, in the above steps, the calculation method of the friction coefficient can adopt two specific implementation manners: In the first specific implementation manner, calculating the friction coefficient may specifically include: calculating the Re number according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipeline, and the dynamic viscosity of the fluid; calculating the friction coefficient through an implicit equation according to the Re number, the outer diameter of the pipeline, and the pipeline roughness; and while calculating the friction coefficient, using the Newton iteration method to gradually approximate the root of the implicit equation through local linearity, and updating the friction coefficient in each iteration.

[0052] In implementation, during the process of calculating the friction coefficient, the Re number can be calculated first according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipeline, and the dynamic viscosity of the fluid by using the following formula (8): ; (8) wherein, represents the dynamic viscosity of the fluid. The above formula (8) is used to judge the flow state (laminar flow or turbulent flow) of the fluid, and comprehensively reflects the influence of factors such as fluid flow velocity, density, viscosity, and pipeline size on the flow.

[0053] Then, according to the Re number, the outer diameter of the pipeline and the pipeline roughness, the friction coefficient is calculated by using the following formula (9) through an implicit equation: ; (9) wherein, represents the pipeline roughness, and the unit is meter. The above formula (9) is an implicit equation, that is, the friction coefficient appears on both sides of the equation and cannot be directly solved. Therefore, in the present invention, while calculating the friction coefficient, the Newton iteration method is used for iterative calculation. Specifically, the root of the implicit equation can be gradually approximated through local linearity, and the friction coefficient is updated in each iteration, which is suitable for high-precision industrial standard calculations. In addition, numerical solutions can also be carried out with the help of software tools (such as Excel iterative calculation, professional fluid calculation software, etc.) to accurately analyze and design the pipelines and ducts in the fluid transportation system.

[0054] In the second specific implementation manner, calculating the friction coefficient may specifically include: calculating the Re number according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipeline, and the dynamic viscosity of the fluid; calculating the first intermediate variable according to the Re number and the pipeline roughness; and calculating the second intermediate variable according to the Re number; and calculating the friction coefficient through an explicit equation according to the Re number, the first intermediate variable, and the second intermediate variable.

[0055] In implementation, during the process of calculating the friction coefficient, the Re number can be calculated first according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipe, and the dynamic viscosity of the fluid using the above formula (8); then, according to the Re number and the pipe roughness, the first intermediate variable can be calculated using the following formula (10); and according to the Re number, the second intermediate variable can be calculated using the following formula (11); finally, according to the Re number, the first intermediate variable, and the second intermediate variable, the friction coefficient can be calculated using the following formula (12) through the explicit equation: ; (10) ; (11) ; (12) wherein, represents the first intermediate variable, represents the second intermediate variable. The above formula (12) avoids implicit solution. It belongs to an explicit equation, and the friction coefficient can be directly calculated given parameters such as the Re number , without iterative solution. Compared with the implicit equation, the error is less than , and it can be calculated quickly, realized by real-time simulation or programming.

[0056] In practical applications, if high precision is required, formula (9) can be used to calculate the friction coefficient; if a quick calculation result is needed, (12) can be used to calculate the friction coefficient.

[0057] It should be noted that the above formulas (5)-(12) can be used as the instantaneous condensation amount calculation model.

[0058] In the present invention, for the characteristic comparison between the heat escape condensation amount and the instantaneous condensation amount, reference can be made to Table 1.

[0059] Table 1 Characteristic comparison between the heat escape condensation amount and the instantaneous condensation amount

[0060]

[0061] In actual working conditions, the heat escape condensation amount calculation formula can be used; for factors such as heat preservation deterioration and dynamic effects, an empirical correction coefficient is introduced, and the instantaneous condensation amount calculation formula can be used. The total condensed water is the sum of the heat escape condensation amount and the instantaneous condensation amount.

[0062] For the steam pipe network condensed water distribution prediction method provided by the present invention, some parameters can be subjected to sensitivity analysis, as shown in Table 2 for details.

[0063] Table 2 Parameter sensitivity analysis

[0064]

[0065] The present invention can design experiments for the steam pipe network condensate distribution prediction method according to the content of Table 3, and Table 4 shows the result comparison.

[0066] Table 3 Experimental Design

[0067]

[0068] Table 4 Result Comparison

[0069]

[0070] Based on the basic principles of thermodynamics, the present invention establishes a mathematical model, considers multiple condensation mechanisms, and the prediction results are more accurate. The multi-parameter coupling model reduces the average error from 22.6% to 4.3%.

[0071] The present invention can achieve prediction by using the data of the Supervisory Control And Data Acquisition (SCADA) system without additional hardware devices, and can quickly respond to the changes in the pipe network topology and the adjustment of operating parameters, support dynamic prediction, provide a scientific basis for the optimal layout of steam traps and the formulation of operating strategies, significantly improve the energy efficiency of the steam system, and support complex working conditions such as inclined pipes and deteriorated insulation.

[0072] Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware, but in many cases, the former is a better implementation method.

[0073] The embodiments of the present application also provide a steam pipe network condensate distribution prediction device. Figure 2 It is a schematic structural diagram of the steam pipe network condensate distribution prediction device provided by the embodiments of the present invention. From the perspective of functional modules, as Figure 2 shown, the device includes: A model establishment module 10, configured to establish a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate amount calculation model and an instantaneous condensate amount calculation model; A data input module 11, configured to input the pipe network basic data including gas source parameters and pipe parameters, and the steam state parameters of each node of the pipe network into the condensate distribution prediction model; A condensate amount calculation module 12, configured to calculate the heat escape condensate amount by using the heat escape condensate amount calculation model and calculate the instantaneous condensate amount by using the instantaneous condensate amount calculation model; A result output module 13, configured to output the condensate distribution prediction result according to the sum of the heat escape condensate amount and the instantaneous condensate amount.

[0074] In the above-mentioned condensate distribution prediction device provided by the embodiments of the present invention, through the interaction of the above four modules, a condensate distribution prediction model can be established between the gas source parameters, pipeline parameters, steam state parameters and condensate generation amount. The heat escape condensate amount calculation model is used to calculate the heat escape condensate amount, and the instantaneous condensation amount calculation model is used to calculate the instantaneous condensation amount. According to the sum of the heat escape condensate amount and the instantaneous condensation amount, real-time calculation at the second level can be achieved, quickly and accurately predicting the condensate distribution in the pipeline network, reducing the average error, with low cost and strong adaptability, providing data support for the operation optimization of the steam pipeline network.

[0075] Since the embodiments of the steam pipeline network condensate distribution prediction device part correspond to the embodiments of the steam pipeline network condensate distribution prediction method part, the descriptions of the features in the corresponding embodiments of the steam pipeline network condensate distribution prediction device can refer to the relevant descriptions of the corresponding embodiments of the steam pipeline network condensate distribution prediction method, which will not be elaborated here one by one. And it has the same beneficial effects as the above-mentioned steam pipeline network condensate distribution prediction method.

[0076] An embodiment of the present application further provides an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above embodiments of the steam pipeline network condensate distribution prediction method.

[0077] An embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored. The computer program is configured to execute the steps in any one of the above embodiments of the steam pipeline network condensate distribution prediction method when running.

[0078] In an exemplary embodiment, the above computer-readable storage medium may include, but is not limited to: USB flash drive, read-only memory (abbreviated as ROM), random access memory (abbreviated as RAM), mobile hard disk, magnetic disk or optical disc and other various media that can store computer programs.

[0079] An embodiment of the present invention further provides a computer program product. The above computer program product includes a computer program, and when the computer program is executed by a processor, it implements the steps in any one of the above embodiments of the steam pipeline network condensate distribution prediction method.

[0080] An embodiment of the present invention further provides another computer program product, including a non-volatile computer-readable storage medium. The non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the steps in any one of the above embodiments of the steam pipeline network condensate distribution prediction method.

[0081] Those skilled in the art may further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in a hardware or software manner 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, but such implementation should not be considered to exceed the scope of the present invention.

[0082] The above has introduced in detail the method, device, equipment, and medium for predicting the condensate water distribution in a steam pipe network provided by the present invention. Specific examples are used herein to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention. It should be noted that for those of ordinary skill in the art in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection scope of the present invention.

Claims

1. A method for predicting the condensate distribution in a steam pipe network, characterized in that, Including: Establish a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate amount calculation model and an instantaneous condensate amount calculation model; Input the gas source parameters, pipeline parameters, and steam state parameters of each node of the pipe network into the condensate distribution prediction model; Use the heat escape condensate amount calculation model to calculate the heat escape condensate amount, and use the instantaneous condensate amount calculation model to calculate the instantaneous condensate amount; Output the condensate distribution prediction result according to the sum of the heat escape condensate amount and the instantaneous condensate amount.

2. The method for predicting the condensate distribution in a steam pipe network according to claim 1, wherein Calculating the heat escape condensate amount includes: Calculate the heat loss per unit pipe length with insulation parameters; Calculate the heat escape condensate amount according to the latent heat of phase change, the pipe length, and the heat loss per unit pipe length with insulation parameters.

3. The method for predicting the condensate water distribution in a steam pipe network according to claim 2, wherein, Calculating the heat loss per unit pipe length with insulation parameters includes: Calculate the heat loss per unit pipe length with insulation parameters according to the steam temperature, the ambient temperature, the thermal conductivity of the insulation material, the outer diameter of the pipe, the outer diameter of the insulation layer, and the ambient convection coefficient.

4. The method for predicting the condensate water distribution in a steam pipe network according to claim 1, wherein, Calculating the instantaneous condensate amount includes: Calculate the two-phase pressure drop and the flow pressure drop, and obtain the total pressure drop according to the sum of the two-phase pressure drop and the flow pressure drop; Calculate the instantaneous condensate amount according to the total pressure drop, the change value of steam dryness, the steam mass, the pipeline input pressure, and the condensation gain factor.

5. The method for predicting the condensate distribution in a steam pipe network according to claim 4, wherein, Calculating the two-phase pressure drop includes: Calculate the friction coefficient; Calculate the pipeline elevation difference according to the pipe length and the pipeline inclination angle; Calculate the two-phase pressure drop according to the friction coefficient, the pipeline elevation difference, the pipe length, the outer diameter of the pipe, the fluid density, and the average flow velocity of the fluid.

6. The method for predicting the condensate distribution in a steam pipe network according to claim 5, wherein Calculating the friction coefficient includes: Calculate the Re number according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipe, and the dynamic viscosity of the fluid; Calculate the friction coefficient through an implicit equation according to the Re number, the outer diameter of the pipe, and the pipe roughness; While calculating the friction coefficient, use the Newton iteration method to gradually approximate the root of the implicit equation through local linearity, and update the friction coefficient in each iteration.

7. The method for predicting the condensate distribution in a steam pipe network according to claim 5, wherein, Calculating the friction coefficient includes: Calculate the Re number according to the fluid density, the average flow velocity of the fluid, the outer diameter of the pipe, and the dynamic viscosity of the fluid; Calculate the first intermediate variable according to the Re number and the pipe roughness; and calculate the second intermediate variable according to the Re number; Calculate the friction coefficient through an explicit equation according to the Re number, the first intermediate variable, and the second intermediate variable.

8. A condensate water distribution prediction device for a steam pipe network, characterized in that, Including: A model establishment module for establishing a condensate distribution prediction model; the condensate distribution prediction model includes a heat escape condensate amount calculation model and an instantaneous condensate amount calculation model; A data input module for inputting the basic pipe network data including gas source parameters and pipeline parameters, and the steam state parameters of each node of the pipe network into the condensate distribution prediction model; A condensate amount calculation module for using the heat escape condensate amount calculation model to calculate the heat escape condensate amount, and using the instantaneous condensate amount calculation model to calculate the instantaneous condensate amount; A result output module for outputting the condensate distribution prediction result according to the sum of the heat escape condensate amount and the instantaneous condensate amount.

9. An electronic device, characterized in that, Including: A memory for storing computer programs; A processor for implementing the steps of the steam pipe network condensate distribution prediction method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the condensate water distribution prediction method for a steam pipe network according to any one of claims 1 to 7 are implemented.

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