LNG Storage Tank Liquefaction BOG Generation Quantity Prediction Method Based on Heat Exchange and Related Devices

Abstract

The present invention discloses a method and related device for predicting the generation amount of liquefied BOG in an LNG storage tank based on heat exchange, belonging to the technical field of production prediction, including: obtaining the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank; constructing a dynamic model of internal heat exchange in the LNG storage tank; obtaining the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and obtaining the external surrounding environment parameters of the LNG storage tank; inputting the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external surrounding environment parameters of the LNG storage tank into the dynamic model of internal heat exchange in the LNG storage tank, predicting the BOG generation rate of each height layer in the LNG storage tank, and calculating the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank. This method and related device can accurately predict the BOG generation amount of the LNG storage tank.

Description

Technical Field

[0001] The present invention belongs to the technical field of production prediction, and relates to a method and related device for predicting the generation amount of liquefied BOG in an LNG storage tank based on heat exchange. Background Technique

[0002] During the storage and transportation of an LNG (Liquefied Natural Gas) storage tank, affected by factors such as environmental temperature, the adiabatic performance of the storage tank, and internal heat exchange, the LNG inside the LNG storage tank will inevitably evaporate to generate BOG (Boil-Off Gas). The generation of BOG will not only affect the stability of the internal pressure of the LNG storage tank, but may also cause energy loss and even affect subsequent gasification transportation, reliquefaction recovery, and safety management. Therefore, accurately predicting the generation amount of BOG in the LNG storage tank is of great significance for optimizing the operation of the LNG storage tank, improving energy utilization efficiency, and reducing safety risks.

[0003] At present, the prediction methods for the generation amount of BOG mainly include empirical formula estimation, pressure change method, and mathematical model method based on heat exchange. Among them, the empirical formula estimation method usually performs approximate calculations based on the design parameters and historical operation data of the LNG storage tank, but it is difficult to consider the influence of different environmental factors, and the prediction accuracy is low; the pressure change method calculates the BOG amount by monitoring the change rate of the internal pressure of the storage tank, but it is easily affected by the change of liquid level and the fluctuation of operating conditions, and the applicability is limited; the mathematical model method based on heat exchange uses the thermophysical properties of the storage tank, external environmental parameters, and LNG physical property parameters to establish a heat exchange calculation model, which improves the prediction accuracy to a certain extent. However, the existing methods mostly use single temperature or static heat balance calculation, and do not fully consider the temperature stratification inside the storage tank and the influence of dynamic changes in the external environment on the latent heat of vaporization, so the prediction accuracy is poor. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned disadvantages of the prior art, and provide a method and related device for predicting the generation amount of liquefied BOG in an LNG storage tank based on heat exchange, which can accurately predict the BOG generation amount of the LNG storage tank.

[0005] To achieve the above purpose, the present invention discloses a method for predicting the generation amount of liquefied BOG in an LNG storage tank based on heat exchange, including:

[0006] Obtain the adiabatic performance parameters of the LNG storage tank, the thermophysical properties of LNG, and the structural parameters of the LNG storage tank;

[0007] Based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties of LNG, and the structural parameters of the LNG storage tank, construct a dynamic model of internal heat exchange in the LNG storage tank;

[0008] Obtain the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and obtain the external ambient environment parameters of the LNG storage tank;

[0009] Input the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external ambient environment parameters of the LNG storage tank into the internal heat exchange dynamic model of the LNG storage tank, predict the BOG generation rate of each height layer in the LNG storage tank, and calculate the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank.

[0010] A further improvement of the method for predicting the liquefied BOG generation amount of an LNG storage tank based on heat exchange according to the present invention is as follows:

[0011] Furthermore, the adiabatic performance parameters of the LNG storage tank include the heat flux density of the LNG storage tank wall ; the thermophysical properties parameters of the LNG include the latent heat of vaporization of the LNG ; the structural parameters of the LNG storage tank include the wall thickness of the LNG storage tank .

[0012] Furthermore, the internal heat exchange dynamic model of the LNG storage tank is composed of the total heat input equation of the LNG storage tank, the heat transfer equation of the LNG storage tank wall, the LNG vaporization mass calculation equation, and the LNG temperature change equation.

[0013] Furthermore, the total BOG generation amount of the LNG storage tank is:

[0014]

[0015] wherein, is the number of layers, is the BOG generation rate of the th height layer in the LNG storage tank.

[0016] Furthermore, the BOG generation rate of the th height layer in the LNG storage tank is:

[0017]

[0018]

[0019] wherein, is the corrected theoretical vaporization mass of the LNG, is the liquid phase temperature of the th height layer in the LNG storage tank, is the gas phase temperature of the height layer in the LNG storage tank, is the corrected total heat input, is the heat transferred through the wall of the LNG storage tank per unit time, is the adjustment coefficient, is the latent heat of vaporization of the LNG mixture, is the average temperature of the LNG in the LNG storage tank.

[0020] Furthermore, the corrected total heat input is:

[0021]

[0022] where is the empirical correction term, is:

[0023] ;

[0024] where is the standard humidity, is the temperature correction coefficient, is the humidity correction coefficient, is the wind speed correction coefficient, is the temperature of the external surrounding environment of the LNG storage tank, is the humidity of the external surrounding environment of the LNG storage tank, is the wind speed of the external surrounding environment of the LNG storage tank, is the total heat entering the LNG storage tank per unit time.

[0025] Furthermore, the liquid phase temperature of the height layer in the LNG storage tank and the gas phase temperature of the height layer in the LNG storage tank are:

[0026]

[0027]

[0028] where is the initial temperature of the liquid phase in the LNG storage tank, is the initial temperature of the gas phase in the LNG storage tank, is the stratification height of the liquid phase, is the stratification height of the gas phase, is the stratification temperature gradient of the liquid phase in the LNG storage tank, is the stratification temperature gradient of the gas phase in the LNG storage tank.

[0029] The present invention discloses a prediction system for the generation amount of liquefied BOG in an LNG storage tank based on heat exchange, including:

[0030] A first acquisition module for acquiring the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank;

[0031] A construction module for constructing a dynamic heat exchange model inside the LNG storage tank based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank;

[0032] A second acquisition module for acquiring the stratified temperature gradient of the liquid phase inside the LNG storage tank and the stratified temperature gradient of the gas phase inside the LNG storage tank, and acquiring the external ambient parameters of the LNG storage tank;

[0033] A prediction module for inputting the stratified temperature gradient of the liquid phase inside the LNG storage tank, the stratified temperature gradient of the gas phase inside the LNG storage tank, and the external ambient parameters of the LNG storage tank into the dynamic heat exchange model inside the LNG storage tank to predict the total generation amount of BOG in the LNG storage tank.

[0034] The present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the prediction method for the generation amount of liquefied BOG in the LNG storage tank based on heat exchange are implemented.

[0035] The present invention discloses a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the prediction method for the generation amount of liquefied BOG in the LNG storage tank based on heat exchange are implemented.

[0036] The present invention has the following beneficial effects:

[0037] When the method and related device for predicting the generation amount of liquefied BOG in an LNG storage tank based on heat exchange according to the present invention are specifically operated, the adiabatic performance parameters of the LNG storage tank, the thermophysical parameters of the LNG, and the structural parameters of the LNG storage tank are comprehensively considered to construct a dynamic model of internal heat exchange in the LNG storage tank, making the internal heat exchange in the LNG storage tank more in line with the real environment. At the same time, the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external ambient parameters of the LNG storage tank are input into the dynamic model of internal heat exchange in the LNG storage tank to predict the total generation amount of BOG in the LNG storage tank. Among them, based on the method of multi-source data input, the predicted result can adapt to different climate conditions, avoiding the limitations of single-parameter prediction. At the same time, the total generation amount of BOG in the LNG storage tank is predicted based on the stratified temperature gradient to improve the refinement degree of the prediction, making the prediction result of the total generation amount of BOG more accurate and reliable. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings forming a part of the present invention are used to provide a further understanding of the present invention. The schematic embodiments and descriptions thereof of the present invention are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0039] Figure 1 is a flowchart of the method of the present invention;

[0040] Figure 2 is a system structure diagram of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] 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 some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0042] In the description of the present invention, it should be understood that the terms "include" and "comprise" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0043] It should also be understood that the terms used in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0044] It should be further understood that the term "and / or" used in the specification and appended claims of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations. For example, A and / or B can represent three cases: A exists alone, A and B exist simultaneously, and B exists alone. Additionally, in the present invention, the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0045] It should be understood that although terms such as first, second, and third may be used in the embodiments of the present invention to describe preset ranges, etc., these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from each other. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0046] Depending on the context, the word "if" as used herein can be interpreted as "when" or "while" or "in response to determining" or "in response to detecting". Similarly, depending on the context, the phrase "if determined" or "if detected (stated condition or event)" can be interpreted as "when determined" or "in response to determining" or "when detected (stated condition or event)" or "in response to detecting (stated condition or event)".

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. Usually, the components of the present invention described and shown in the accompanying drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed present invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0048] Various structural schematic diagrams according to the disclosed embodiments of the present invention are shown in the drawings. These figures are not drawn to scale, where some details are enlarged for the purpose of clear expression, and some details may be omitted. The shapes of various regions and layers shown in the figures and their relative sizes and positional relationships are only exemplary, and may actually deviate due to manufacturing tolerances or technical limitations. And those skilled in the art can design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0049] Embodiment 1

[0050] Reference Figure 1 , the method for predicting the liquefied BOG generation amount of the LNG storage tank based on heat exchange according to the present invention includes the following steps:

[0051] 1) Obtain the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank;

[0052] The adiabatic performance parameters of the LNG storage tank include the heat flux density on the wall surface of the LNG storage tank , wherein, the heat flux density on the wall surface of the LNG storage tank is measured by a heat flux sensor , , is the thermal conductivity of the insulation layer in the LNG storage tank, is the temperature of the inner wall surface of the LNG storage tank, is the temperature of the outer wall surface of the LNG storage tank, is the thickness of the insulation layer in the LNG storage tank.

[0053] The thermophysical properties parameters of the LNG include the latent heat of vaporization of the LNG , the latent heat of vaporization of the LNG is measured by an on-line LNG composition analyzer, wherein, , is the mole fraction of the th component in the LNG, is the latent heat of vaporization of the th component in the LNG.

[0054] The structural parameters of the LNG storage tank include the wall thickness of the LNG storage tank , wherein, , is the design pressure inside the LNG storage tank, is the inner diameter of the LNG storage tank, is the allowable stress of the material used for the LNG storage tank.

[0055] 2) Based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank, construct a dynamic model of heat exchange inside the LNG storage tank;

[0056] It should be noted that the dynamic model of heat exchange inside the LNG storage tank includes the total heat input equation of the LNG storage tank, the heat transfer equation of the LNG storage tank wall, the LNG vaporization mass calculation equation, and the LNG temperature change equation.

[0057] Among them, based on the heat flux density on the wall surface of the LNG storage tank the total heat input equation of the LNG storage tank is constructed as:

[0058]

[0059] Among them, is the total heat entering the LNG storage tank per unit time, is the outer surface area of the LNG storage tank.

[0060] Based on the wall thickness of the LNG storage tank The heat transfer equation of the LNG storage tank wall is constructed as:

[0061]

[0062] Among them, is the heat transferred through the LNG storage tank wall per unit time, is the thermal conductivity of the material used for the LNG storage tank wall.

[0063] The LNG temperature change equation is expressed as:

[0064]

[0065] Among them, is the average temperature of the LNG in the LNG storage tank, is time, is the mass of the LNG in the LNG storage tank, is the specific heat capacity of the LNG.

[0066] Based on the latent heat of vaporization of the LNG The calculation equation for the vaporization mass of the LNG per unit time is established as:

[0067]

[0068] Among them, is the theoretical vaporization mass of the LNG per unit time, is the latent heat of vaporization of the LNG considering the influence of the current average temperature of the LNG, specifically:

[0069]

[0070] Among them, is the standard temperature The latent heat of vaporization of the LNG at is the latent heat of vaporization correction coefficient related to the LNG composition, used to characterize the influence of temperature change on the latent heat of vaporization, The value range is:

[0071] For standard LNG, that is, the methane content of the LNG > 90%, then The value of .

[0072] For ethane / propane-rich LNG, i.e., the methane content of LNG is , then the value of is taken as

[0073] For nitrogen-rich LNG, i.e., the methane content of LNG < 80%, then the value of is taken as

[0074] 3) Obtain the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and obtain the external surrounding environment parameters of the LNG storage tank;

[0075] Specifically, the external surrounding environment parameters of the LNG storage tank include the temperature, humidity and wind speed of the external surrounding environment of the LNG storage tank. A plurality of temperature sensors are arranged vertically along the liquid phase and the gas phase inside the LNG storage tank, and the temperature at different heights in the liquid phase inside the LNG storage tank is measured by each temperature sensor and the temperature at different heights in the gas phase . According to the temperature at different heights in the liquid phase inside the LNG storage tank calculate the stratified temperature gradient of the liquid phase in the LNG storage tank ; according to the temperature at different heights in the gas phase inside the LNG storage tank calculate the stratified temperature gradient of the gas phase in the LNG storage tank ; detect the temperature and humidity of the external surrounding environment of the LNG storage tank through an environmental temperature and humidity sensor, and measure the wind speed of the external surrounding environment of the LNG storage tank through an anemometer . It should be noted that the present invention performs synchronous data acquisition at a preset time interval .

[0076] The stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank are respectively:

[0077]

[0078]

[0079] Among them, is the vertical distance between adjacent temperature sensors in the liquid phase of the LNG storage tank, is the vertical distance between adjacent temperature sensors in the gas phase of the LNG storage tank.

[0080] 4) Input the obtained liquid-phase stratified temperature gradient in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external ambient environment parameters of the LNG storage tank into the internal heat exchange dynamic model of the LNG storage tank to predict the BOG generation rate of each height layer in the LNG storage tank, and calculate the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank.

[0081] The specific process of step 4) is as follows:

[0082] 41) Calculate the temperature distribution of each height layer in the LNG storage tank. Among them, the liquid-phase temperature of the height layer in the LNG storage tank and the gas-phase temperature of the height layer in the LNG storage tank are:

[0083]

[0084]

[0085] Among them, is the initial temperature of the liquid phase in the LNG storage tank, is the initial temperature of the gas phase in the LNG storage tank, is the stratified height of the liquid phase, is the stratified height of the gas phase.

[0086] 42) Calculate the corrected total heat input according to the temperature and humidity of the external ambient environment of the LNG storage tank and the wind speed of the external ambient environment of the LNG storage tank. Among them, the corrected total heat input is:

[0087]

[0088] Among them, is an empirical correction term used to correct the additional heat exchange caused by environmental changes. Specifically, is:

[0089] ;

[0090] Among them, is the standard humidity, is the temperature correction coefficient, used to characterize the influence of the environmental temperature on the heat exchange of the LNG storage tank, is the humidity correction coefficient, used to characterize the influence of humidity on heat transfer, is the wind speed correction coefficient, used to characterize the influence of wind speed on heat transfer.

[0091] 43) Take the corrected total heat input as the total heat entering the LNG storage tank per unit time , and calculate the temperature change of LNG ;

[0092] 44) Calculate the corrected theoretical vaporization mass of LNG , where ;

[0093] 45) Calculate the BOG generation rate at different height layers in the LNG storage tank as:

[0094]

[0095] where is the adjustment coefficient, affected by the components of LNG and the operating conditions of the LNG storage tank. Specifically:

[0096] For a standard cryogenic storage tank, i.e., at atmospheric pressure storage, then the value of is taken, applicable to large LNG storage tanks.

[0097] For a medium-pressure storage tank, i.e., the pressure range in the LNG storage tank is , then the value of is taken, applicable to relatively small LNG storage tanks.

[0098] For a high-pressure storage tank, i.e., the pressure in the LNG storage tank > 0.5 MPa, then the value of .

[0099] 46) Calculate the total BOG generation amount according to the BOG generation rate at all height layers in the LNG storage tank , where is the number of layers.

[0100] Example Two

[0101] Refer to Figure 2 , this example discloses a prediction system for the liquefied BOG generation amount of an LNG storage tank based on heat exchange, including:

[0102] The first acquisition module is used to acquire the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of LNG, and the structural parameters of the LNG storage tank;

[0103] A construction module for constructing a dynamic model of internal heat exchange of an LNG storage tank based on the heat insulation performance parameters of the LNG storage tank, the thermophysical properties of LNG, and the structural parameters of the LNG storage tank;

[0104] A second acquisition module for acquiring the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and acquiring the external ambient environment parameters of the LNG storage tank;

[0105] A prediction module for inputting the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external ambient environment parameters of the LNG storage tank into the dynamic model of internal heat exchange of the LNG storage tank, predicting the BOG generation rate of each height layer in the LNG storage tank, and calculating the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank.

[0106] In the embodiments of the present invention, the division of the modules is illustrative, only a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of the present invention, the functional modules can be integrated in one processor, or can exist independently physically, or two or more modules can be integrated in one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0107] Embodiment III

[0108] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the LNG storage tank liquefied BOG generation amount prediction method based on heat exchange are implemented. For example, it includes: obtaining the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank; constructing a dynamic heat exchange model inside the LNG storage tank based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of the LNG, and the structural parameters of the LNG storage tank; obtaining the stratified temperature gradient of the liquid phase inside the LNG storage tank and the stratified temperature gradient of the gas phase inside the LNG storage tank, and obtaining the external surrounding environment parameters of the LNG storage tank; inputting the stratified temperature gradient of the liquid phase inside the LNG storage tank, the stratified temperature gradient of the gas phase inside the LNG storage tank, and the external surrounding environment parameters of the LNG storage tank into the dynamic heat exchange model inside the LNG storage tank, predicting the BOG generation rate of each height layer inside the LNG storage tank, and calculating the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer inside the LNG storage tank. Among them, the memory may include internal memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk memory, etc.; the processor, network interface, and memory are interconnected through an internal bus, and this internal bus can be an Industry Standard Architecture bus, a Peripheral Component Interconnect standard bus, an Extended Industry Standard Architecture bus, etc., and the bus can be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include internal memory and non-volatile memory, and provides instructions and data to the processor.

[0109] Embodiment 4

[0110] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, it implements the steps of the method for predicting the production amount of liquefied BOG in an LNG storage tank based on heat exchange, including: obtaining the adiabatic performance parameters of the LNG storage tank, the thermophysical properties of LNG, and the structural parameters of the LNG storage tank; constructing a dynamic model of internal heat exchange in the LNG storage tank based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties of LNG, and the structural parameters of the LNG storage tank; obtaining the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and obtaining the external ambient environment parameters of the LNG storage tank; inputting the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external ambient environment parameters of the LNG storage tank into the dynamic model of internal heat exchange in the LNG storage tank to predict the BOG generation rate of each height layer in the LNG storage tank, and calculating the total BOG production amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disc, magnetic disk, etc.

[0111] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows or multiple flows and / or blocks Figure 1 one or more of the blocks or multiple blocks.

[0113] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more of the processes Figure 1 and / or blocks Figure 1 specified in one or more of the processes and / or blocks.

[0114] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more of the processes Figure 1 and / or blocks Figure 1 specified in one or more of the processes and / or blocks.

[0115] Other embodiments of the present invention will be readily apparent to those skilled in the art upon consideration of the specification and disclosure of the invention. The present invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include known common knowledge or conventional technical means in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are pointed out by the following claims.

[0116] It should be understood that the present invention is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present invention is limited only by the appended claims.

[0117] The above are only preferred embodiments of the present invention and do not impose any limitation on the present invention. Any simple modifications, changes, and equivalent structural changes made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solutions of the present invention.

Claims

1. A method for predicting the production amount of liquefied BOG in an LNG storage tank based on heat exchange, characterized in that, Including: Obtain the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of LNG, and the structural parameters of the LNG storage tank; Based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of LNG, and the structural parameters of the LNG storage tank, construct a dynamic model of internal heat exchange of the LNG storage tank; Obtain the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and obtain the external surrounding environment parameters of the LNG storage tank; Input the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external surrounding environment parameters of the LNG storage tank into the dynamic model of internal heat exchange of the LNG storage tank, predict the BOG generation rate of each height layer in the LNG storage tank, and calculate the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank; The total BOG generation amount of the LNG storage tank is as follows: Among them, is the number of layers, is the BOG generation rate of the height layer in the LNG storage tank; The BOG generation rate at the height layer inside the LNG storage tank is as follows: Among them, is the corrected theoretical vaporization mass of LNG, is the liquid phase temperature of the height layer in the LNG storage tank, is the gas phase temperature of the height layer in the LNG storage tank, is the corrected total heat input, is the heat transferred through the wall of the LNG storage tank per unit time, is the adjustment coefficient, is the latent heat of vaporization of the LNG mixture, is the average temperature of the LNG in the LNG storage tank.

2. The method for predicting the generation amount of liquefied BOG in an LNG storage tank based on heat exchange according to claim 1, wherein The adiabatic performance parameters of the LNG storage tank include the heat flux density on the wall of the LNG storage tank ; The thermophysical parameters of the LNG include the latent heat of vaporization of the LNG ; The structural parameters of the LNG storage tank include the wall thickness of the LNG storage tank .

3. The method for predicting the liquefied BOG generation amount of an LNG storage tank based on heat exchange according to claim 1, wherein The dynamic model of internal heat exchange of the LNG storage tank is composed of the total heat input equation of the LNG storage tank, the heat transfer equation of the LNG storage tank wall, the LNG vaporization mass calculation equation, and the LNG temperature change equation.

4. The method for predicting the production amount of liquefied BOG in an LNG storage tank based on heat exchange according to claim 1, wherein, The corrected total heat input is as follows: Among them, is an empirical correction term, which is: ； Among them, is the standard humidity, is the temperature correction coefficient, is the humidity correction coefficient, is the wind speed correction coefficient, is the temperature of the external surrounding environment of the LNG storage tank, is the temperature of the outer wall surface of the LNG storage tank, is the humidity of the external surrounding environment of the LNG storage tank, is the wind speed of the external surrounding environment of the LNG storage tank, is the total heat entering the LNG storage tank per unit time.

5. The method for predicting the liquefied BOG generation amount of an LNG storage tank based on heat exchange according to claim 1, wherein The liquid phase temperature of the height layer in the LNG storage tank and the gas phase temperature of the height layer in the LNG storage tank are as follows: Among them, is the initial temperature of the liquid phase in the LNG storage tank, is the initial temperature of the gas phase in the LNG storage tank, is the stratification height of the liquid phase, is the stratification height of the gas phase, is the stratification temperature gradient of the liquid phase in the LNG storage tank, is the stratification temperature gradient of the gas phase in the LNG storage tank.

6. A prediction system for the liquefied BOG generation amount of an LNG storage tank based on heat exchange, characterized in that, Including: A first acquisition module for obtaining the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of LNG, and the structural parameters of the LNG storage tank; A construction module for constructing a dynamic model of internal heat exchange of the LNG storage tank based on the adiabatic performance parameters of the LNG storage tank, the thermophysical properties parameters of LNG, and the structural parameters of the LNG storage tank; A second acquisition module for obtaining the stratified temperature gradient of the liquid phase in the LNG storage tank and the stratified temperature gradient of the gas phase in the LNG storage tank, and obtaining the external surrounding environment parameters of the LNG storage tank; A prediction module for inputting the stratified temperature gradient of the liquid phase in the LNG storage tank, the stratified temperature gradient of the gas phase in the LNG storage tank, and the external surrounding environment parameters of the LNG storage tank into the dynamic model of internal heat exchange of the LNG storage tank, predicting the BOG generation rate of each height layer in the LNG storage tank, and calculating the total BOG generation amount of the LNG storage tank according to the BOG generation rate of each height layer in the LNG storage tank; The total BOG generation amount of the LNG storage tank is as follows: Among them, is the number of layers, is the BOG generation rate of the height layer in the LNG storage tank; The BOG generation rate of the height layer inside the LNG storage tank is as follows: Wherein, is the corrected theoretical vaporization mass of LNG, is the liquid phase temperature at the height layer in the LNG storage tank, is the gas phase temperature at the height layer in the LNG storage tank, is the corrected total heat input, is the heat transferred through the wall of the LNG storage tank per unit time, is the adjustment coefficient, is the latent heat of vaporization of the LNG mixture, is the average temperature of the LNG in the LNG storage tank.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method for predicting the liquefied BOG generation amount of the LNG storage tank based on heat exchange according to any one of claims 1-5 are implemented.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method for predicting the liquefied BOG generation amount of the LNG storage tank based on heat exchange according to any one of claims 1-5 are implemented.

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