Boil-off gas recovery reliquefication device and control method and system thereof

Abstract

The application discloses a BOG recycling and reliquefaction device and a control method and system thereof, wherein the device comprises a BOG processing assembly, a cascade cold energy recovery heat exchanger group and a gas-liquid separation and reflux assembly which are sequentially communicated; the BOG processing assembly is used for collecting the evaporated gas generated when the corresponding target liquid hydrogen tank car is unloaded and the evaporated gas generated when the liquid hydrogen storage tank is at rest; and is also used for outputting the corresponding pressurized and cooled gas to the cascade cold energy recovery heat exchanger group for cooling and liquefaction after the collected evaporated gas is pressurized and cooled; the cascade cold energy recovery heat exchanger group is used for allowing the liquid hydrogen unloaded from the target liquid hydrogen tank car to exchange heat with the pressurized and cooled gas, so that the pressurized and cooled gas is liquefied to generate liquefied recycling two-phase flow; and the gas-liquid separation and reflux assembly is used for carrying out gas-liquid separation on the liquefied recycling two-phase flow output by the liquefaction heat exchanger to obtain corresponding recycling liquid hydrogen and reflux tail gas. The application can solve the contradiction between high recycling rate and high energy consumption.

Description

Technical Field

[0001] This invention relates to the field of energy storage technology, and in particular to a BOG recovery and reliquefaction device and its control method and system for a liquid hydrogen storage and transportation facility. Background Technology

[0002] Liquid hydrogen (LH2) has become the preferred method for large-scale, long-distance storage and transportation of hydrogen energy due to its extremely high volumetric energy density. However, liquid hydrogen has an extremely low boiling point (-253°C). During storage, transportation, handling, and unloading, environmental heat leakage causes the liquid inside the storage tank to continuously evaporate, generating boil-off gas (BOG).

[0003] Several general approaches have been developed in the industry for handling cryogenic liquid BOGs, but they all have significant shortcomings when applied to the specific scenario of liquid hydrogen: (1) Traditional direct treatment methods. Direct emission / flare combustion: This is the simplest method, but it wastes resources and generates carbon emissions, which runs counter to the concept of green hydrogen energy, and it also poses high safety risks. Compressed storage or grid connection: BOG is pressurized to medium or high pressure and then stored or injected into the pipeline network. Although this method can recover hydrogen, the energy consumption for hydrogen compression is extremely high (accounting for about 10%-15% of the energy of hydrogen), and it is subject to strict limitations imposed by downstream gas pressure and demand, resulting in poor flexibility.

[0004] (2) Reliquefaction and recovery technology. Independent reliquefaction system: The BOG is recooled and liquefied using an independent cryogenic refrigeration unit (such as a helium Brayton cycle refrigeration unit) and returned to the storage tank. This is the ideal way to achieve near "zero emissions". However, the system needs to independently provide the cooling capacity from room temperature to 20K throughout the process, which consumes a lot of energy and has high operating costs, thus deteriorating the overall economics of liquid hydrogen storage and transportation. Summary of the Invention

[0005] This invention addresses the shortcomings of existing technologies for processing liquid hydrogen BOG, which struggle to balance the demand for high recovery rates with high energy consumption and costs. It provides a BOG recovery and reliquefaction device and its control method and system.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: Firstly, a BOG recovery and reliquefaction device is proposed for recovering and reliquefying the evaporated gas generated during the unloading and settling process of liquid hydrogen storage and transportation facilities, wherein the liquid hydrogen storage and transportation facilities include liquid hydrogen tank trucks and liquid hydrogen storage tanks. Its features include: The BOG processing unit, the cascaded cold energy recovery heat exchanger group, and the gas-liquid separation and reflux unit are connected in sequence. The BOG processing component is used to collect the vapors generated when the target liquid hydrogen tanker is unloaded, as well as the vapors generated when the liquid hydrogen storage tank is left to stand; it is also used to pressurize and cool the collected vapors, and then output the pressurized and cooled gas to the cascaded cold energy recovery heat exchanger group for cooling and liquefaction. The cascaded cold energy recovery heat exchanger assembly is used to exchange heat between the liquid hydrogen unloaded from the target liquid hydrogen tanker and the pressurized cooling gas, so that the pressurized cooling gas is liquefied and a liquefied recovery two-phase flow is generated. The gas-liquid separation and reflux assembly is used to separate the liquefied two-phase flow output from the liquefied heat exchanger into gas and liquid, obtain corresponding recovered liquid hydrogen and reflux tail gas, transport the recovered liquid hydrogen to the corresponding liquid hydrogen storage tank, and transport the reflux tail gas to the BOG processing assembly.

[0007] As one possible implementation method: The cascaded cold energy recovery heat exchanger group includes a refrigeration unit, and also includes a cold energy buffer heat exchanger, a main heat exchanger and a liquefaction heat exchanger cascaded in sequence, wherein the liquefaction heat exchanger is coupled to the cold head of the refrigeration unit. The cold energy buffer heat exchanger is connected to the gas-liquid separation and reflux assembly, the BOG processing assembly and the target liquid hydrogen tanker respectively, and is used to exchange heat between the main unloading liquid hydrogen flow from the target liquid hydrogen tanker and the reflux exhaust gas from the gas-liquid separation and reflux assembly, and to transport the heat-exchanged main unloading liquid hydrogen flow to the main heat exchanger, and to transport the heat-exchanged reflux exhaust gas to the BOG processing assembly. The main heat exchanger is also connected to the BOG processing assembly and the liquid hydrogen storage tank, and is used to pre-cool the pressurized cooling gas by utilizing the cold energy of the main unloading liquid hydrogen flow. The main unloading liquid hydrogen flow after heat exchange enters the liquid hydrogen storage tank. The liquefaction heat exchanger is used to further cool the pressurized cooling gas pre-cooled by the main heat exchanger using the refrigerator, so that it is completely liquefied and outputs a liquefied recovery two-phase flow.

[0008] As one possible implementation method: The main heat exchanger is equipped with a phase change energy storage buffer module, which encapsulates a phase change material with a phase change temperature of 25K-30K.

[0009] As one possible implementation method: A gas-liquid separator is used to separate liquid hydrogen and gas in a liquefied and recovered two-phase flow by using gravity and centrifugal force, to obtain the corresponding recovered liquid hydrogen and reflux tail gas. The liquid phase pipeline is used to directly transport the separated recovered liquid hydrogen back to the storage tank in the station to complete the product recovery. The gas phase reflux pipeline is used to guide the separated reflux tail gas back to the cold energy buffer heat exchanger, and then enter the BOG processing unit through the cold energy buffer heat exchanger.

[0010] As one possible implementation, a combustion power generation module is also included; The gas phase reflux pipeline is connected to the cold energy buffer heat exchanger or the combustion power generation module; When the gas phase reflux pipeline is connected to the combustion power generation module, the reflux exhaust gas is delivered to the combustion power generation module for power generation.

[0011] Secondly, a control method for a BOG recycling and reliquefaction device is proposed, including the following steps; Collect operating data from the BOG recovery and reliquefaction unit; Based on a preset dynamic process model, the state of the BOG recovery and reliquefaction device is simulated in real time based on the currently collected operating data, and the changes in the operating data are predicted to obtain the corresponding prediction results. The health index of each key piece of equipment in the BOG recovery and reliquefaction unit is evaluated based on the operating data. Based on the obtained prediction results and the health index of each key device, the execution parameters of the BOG recycling and reliquefaction unit are calculated to minimize the overall cost. The BOG recycling and reliquefaction device is controlled based on the obtained execution parameters, and the execution effect is continuously monitored.

[0012] As one possible implementation method: A corresponding health analysis model is pre-built for each key piece of equipment. The health analysis model is used to extract the current feature parameters corresponding to each evaluation feature based on the operating condition data. Determine the baseline characteristic parameters corresponding to each evaluation characteristic; The deviation between the current feature parameters and the benchmark feature parameters is calculated in real time. The health index of the key equipment is obtained by weighting the deviation of each evaluation feature. The calculation formula is as follows: ; in: w i The weight of the i-th evaluation feature; The current feature parameter for the i-th evaluated feature; represents the baseline feature parameter for the i-th evaluation feature.

[0013] As one possible implementation method: The comprehensive cost is calculated based on energy consumption cost, virtual equipment maintenance cost, and recovery rate deviation penalty. The energy consumption cost is calculated based on the power consumption of the chiller and compressor and the corresponding time-of-use electricity price; The virtual maintenance cost of each key piece of equipment is negatively correlated with the corresponding health index.

[0014] As one possible implementation, when a start / stop signal of the unloading pump is detected or a step change in the liquid hydrogen flow meter exceeds a set threshold, the dynamic process model is invoked, and based on the prediction results of the dynamic process model, a feedforward compensation control command is generated and issued.

[0015] Thirdly, a control system for a BOG recycling and reliquefaction device is proposed, including: The execution perception module, located in the edge control layer, is used to collect the operating condition data of the BOG recycling and reliquefaction device, and also to control the operation of the BOG recycling and reliquefaction device based on the obtained execution parameters and continuously monitor the execution effect. The optimization control module, located in the cloud, is used to simulate the state of the BOG recycling and reliquefaction unit in real time based on a preset dynamic process model and currently collected operating data, and to predict changes in the operating data to obtain corresponding prediction results. It is also used to evaluate the health index of each key device in the BOG recycling and reliquefaction unit based on the operating data; and to calculate the execution parameters of the BOG recycling and reliquefaction unit when the overall cost is minimized based on the obtained prediction results and the health index of each key device.

[0016] This invention, by adopting the above technical solutions, has significant technical effects: The design of the cascaded cold energy recovery heat exchanger group in this invention can use the inherent cold energy of the unloaded liquid hydrogen flow as the main cold source for processing its own BOG, and undertake 60-80% of the liquefaction load. This reduces the power requirement of the external refrigeration unit by 50%-70%, and the overall energy consumption of the system is reduced by 20%-35% compared with the traditional reliquefaction scheme, fundamentally solving the contradiction between high recovery rate and high energy consumption. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the BOG recycling and reliquefaction device provided in the embodiments of this application; Figure 2 This is another schematic diagram of the BOG recycling and reliquefaction device provided in the embodiments of this application; Figure 3 This is a schematic flowchart of the control method for the BOG recycling and reliquefaction device provided in the embodiments of this application; Figure 4This is a schematic diagram of the average recovery rate of BOG after 72 hours of continuous operation testing in this application case. Detailed Implementation

[0019] The present invention will be further described in detail below with reference to the embodiments. The following embodiments are explanations of the present invention, but the present invention is not limited to the following embodiments.

[0020] Example 1: BOG recovery and reliquefaction device, which is used to efficiently recover and reliquefy the boil-off gas (BOG) generated during the unloading and settling process of liquid hydrogen storage and transportation facilities (such as liquid hydrogen tank truck 10 and liquid hydrogen storage tank 20). like Figure 1 As shown, it includes: a BOG processing unit 100, a cascaded cold energy recovery heat exchanger group 200 and a gas-liquid separation and reflux unit 300 connected in sequence. The BOG processing component 100: Reference Figure 1 The BOG processing component 100 is connected to the cascaded cold energy recovery heat exchanger group 200, as well as the external liquid hydrogen storage tank 20 and the target liquid hydrogen tanker 10. The BOG processing component 100 is used to collect the vapors generated when the target liquid hydrogen tanker 10 is unloaded, as well as the vapors generated when the liquid hydrogen storage tank 20 is left to stand; it is also used to pressurize and cool the collected vapors before outputting them to the cascaded cold energy recovery heat exchanger group 200 for cooling and liquefaction; it is also used to collect the return exhaust gas output by the cascaded cold energy recovery heat exchanger group 200. Reference Figure 1 The BOG processing assembly 100 includes a BOG collection tank 110, a compressor 120, and a cooler 130 connected in sequence. The evaporated gas collected in the BOG collection tank 110 is first pressurized by the compressor 120, then cooled by the cooler 130, and finally enters the cascaded cold energy recovery heat exchanger group 200 to exchange heat with the liquid hydrogen unloaded from the target liquid hydrogen tanker 10. The BOG collection tank 110 is connected to the cascaded cold energy recovery heat exchanger group 200, the external liquid hydrogen storage tank 20, and the corresponding target liquid hydrogen tanker 10, respectively, and is used to store the evaporated gas generated during unloading and settling. The BOG collection tank 110 is used to collect and store the vaporized gas released by the pressure when the target liquid hydrogen tanker 10 is unloaded, and is also used to collect and store the vaporized gas of the corresponding liquid hydrogen storage tank 20 (such as the on-site storage tank) during static evaporation, and is also used to collect the return tail gas output by the cascade cold energy recovery heat exchanger group 200. The compressor 120 is used to pressurize the evaporated gas (e.g., 0.12 MPaA) output from the BOG collection tank 110 to obtain pressurized steam. The pressure range of the pressurized steam is 1.5 - 3.0 MPaA. In this embodiment, it is compressed to 2.0 MPaA to facilitate its efficient liquefaction. In this embodiment, the compressor 120 is an oil-free / film compressor 120 to avoid lubricating oil contaminating the extremely high purity hydrogen. The cooler 130 is used to cool the pressurized steam and output corresponding pressurized cooling gas; Since pressurization causes the evaporating gas to heat up, this embodiment uses a cooler 130 to cool the pressurized steam (e.g., to ambient temperature ~300K) to reduce the heat load entering the main heat exchanger in the cascaded cold energy recovery heat exchanger group 200.

[0021] The cascaded cold energy recovery heat exchanger assembly 200: The cascaded cold energy recovery heat exchanger group 200 is used to exchange heat between the liquid hydrogen unloaded from the target liquid hydrogen tanker 10 and the pressurized cooling gas, so that the pressurized cooling gas is liquefied and a liquefied recovery two-phase flow is generated. Reference Figure 1 The cascaded cold energy recovery heat exchanger group 200 is connected to the gas-liquid separation and reflux assembly 300, the BOG processing assembly 100 (BOG collection tank 110 and cooler 130), and the external target liquid hydrogen tanker 10. The cascaded cold energy recovery heat exchanger is used to exchange heat with the liquid hydrogen unloaded from the target liquid hydrogen tanker 10 and the reflux exhaust gas separated by the gas-liquid separation and reflux assembly 300 to stabilize the unloaded liquid hydrogen flow state and initially recover the cold energy of the circulating cold fluid in the system; it is also used to exchange heat with the pressurized cooling gas output from the BOG processing assembly 100 to facilitate the liquefaction of the pressurized cooling gas.

[0022] Reference Figure 1 The cascaded cold energy recovery heat exchanger group 200 includes a refrigerator, and also includes a cold capacity buffer heat exchanger 210, a main heat exchanger 220 and a liquefaction heat exchanger 230 cascaded in sequence, wherein the liquefaction heat exchanger 230 is coupled to the cold head of the refrigerator. The cold energy buffer heat exchanger 210 is connected to the gas-liquid separation and reflux assembly 300, the BOG collection tank 110 and the target liquid hydrogen tanker 10 to be unloaded, respectively. It is used to exchange heat between the main unloading liquid hydrogen flow (~20K) from the target liquid hydrogen tanker 10 and the extremely low temperature reflux tail gas (~22-25K) from the gas-liquid separation and reflux assembly 300. After the heat exchange is completed, the main unloading liquid hydrogen flow is sent to the main heat exchanger 220 for main cold energy recovery. After the heat exchange is completed, the reflux tail gas returns to the BOG collection tank 110. During this process, the liquid hydrogen is slightly reheated (e.g., raised to ~22K), making its flow state more stable.

[0023] The main heat exchanger 220 is also connected to the cooler 130, and is used to use the cold energy of the unloading main liquid hydrogen flow to deeply pre-cool the pressurized cooling gas, and bear most of the liquefaction cooling load. Cold side (primary side): The main unloading liquid hydrogen flow (~22K) is heat exchanged by the cold buffer heat exchanger 210.

[0024] Hot side (secondary side): pressurized cooling gas (~300K, 2.0 MPaA).

[0025] That is, the main heat exchanger 220 is used to pre-cool the pressurized cooling gas from the main unloading liquid hydrogen flow from the cold buffer heat exchanger 210. After heat exchange, the main unloading liquid hydrogen flow enters the liquid hydrogen storage tank 20, and the pre-cooled pressurized cooling gas enters the liquefaction heat exchanger 230.

[0026] The pressurized cooling gas is deeply cooled to near its critical point of saturation temperature at that pressure by the main unloading liquid hydrogen flow during countercurrent heat exchange. For example, cooling from 300K to 28K-30K; at this point, the pressurized cooling gas has released most of its sensible heat and may enter the gas-liquid two-phase region, where about 60-80% of the total liquefaction cooling load is completed; the liquid hydrogen absorbs heat, and after its temperature rises to about 24-26K, it flows out and continues to enter the liquid hydrogen storage tank 20.

[0027] This embodiment utilizes the liquid hydrogen cooling capacity that would normally be consumed through tank evaporation or environmental heat leakage after unloading, achieving a free internal transfer of cooling energy from the product (liquid hydrogen) to the by-product (BOG).

[0028] Those skilled in the art can design the main heat exchanger 220 themselves. The main unloading liquid hydrogen flow and the pressurized cooling gas can achieve countercurrent heat exchange. In this embodiment, a multi-flow plate-fin heat exchanger (heat exchange area of ​​150㎡, designed liquid hydrogen flow rate of 3000kg / h, BOG flow rate of 50kg / h) is used, which can achieve complete countercurrent heat exchange and maximize the heat transfer temperature difference and efficiency.

[0029] The liquefaction heat exchanger 230 is used to further cool the pressurized cooling gas pre-cooled by the main heat exchanger 220 using a refrigeration unit, so that it is completely liquefied and reaches a certain degree of subcooling, and outputs a liquefied recovery two-phase flow.

[0030] In this embodiment, the refrigerator can be a helium refrigerator or a reverse Brayton cycle refrigerator. Those skilled in the art can choose according to actual needs, and this specification does not limit it.

[0031] In this embodiment, in the liquefaction heat exchanger 230, the nearly saturated pressurized cooling gas (~30K) from the main heat exchanger 220 exchanges heat with the cryogenic refrigerant (such as helium, ~15-18K) from the refrigerator cold head, and is finally cooled to below 20K and completely liquefied. Since the inlet temperature is already extremely low, the chiller only needs to provide about 20-40% of the total cooling capacity. Therefore, its power and size can be reduced by 50%-70% compared to traditional independent reliquefaction systems. For example, in this embodiment, the chiller used has a rated power of 15kW (the traditional solution requires about 45kW).

[0032] As one possible implementation, a phase change energy storage buffer module 240 is added to the main heat exchanger 220 to absorb or release cold energy, smooth out the cold load impact caused by the instantaneous change of BOG production rate or the fluctuation of unloading flow, and improve the robustness of the system. The phase change energy storage buffer module 240 is encapsulated with a phase change material (PCM) with a specific phase change temperature (such as the 25K-30K range). Those skilled in the art can select a suitable phase change material according to actual needs. For example, the phase change materials that can be selected include neon, secondary hydrogen, helium-4 and nitrogen, preferably neon, whose standard boiling point can match the 25K-30K buffer temperature range required by the system.

[0033] The phase change energy storage buffer module 240 is integrated into the shell or flow channel of the main cold energy recovery heat exchanger, or it can be set independently at its inlet and outlet pipelines. Those skilled in the art can set the integration position of the phase change energy storage buffer module 240 according to actual needs, so that the internal phase change material can maintain good thermal contact with the BOG flow path and liquid hydrogen flow path in the main heat exchanger 220.

[0034] The working principle of the phase change energy storage buffer module 240 is as follows: When the instantaneous production rate of BOG suddenly increases (such as at the start of unloading), exceeding the instantaneous cooling energy supply capacity of liquid hydrogen, the PCM absorbs the excess heat load and slows down the temperature rise of the boosted cooling gas.

[0035] When the liquid hydrogen unloading flow fluctuates or is briefly interrupted, the PCM releases its stored cold energy to provide a buffer cold source for the BOG, preventing drastic fluctuations in system temperature and pressure.

[0036] The design of the phase change energy storage buffer module 240 can effectively improve stability and make it more adaptable to dynamic loads.

[0037] Gas-liquid separation and reflux assembly 300: The gas-liquid separation and reflux assembly 300 is used to separate the liquefied recovery two-phase flow output from the liquefaction heat exchanger 230 into gas and liquid, to obtain the corresponding recovered liquid hydrogen and reflux tail gas. The recovered liquid hydrogen is transported to the corresponding liquid hydrogen storage tank 20, and the reflux tail gas is transported to the combined cooling energy recovery heat exchanger group (cooling buffer heat exchanger 210). The reflux tail gas is used to perform micro-reheating on the main unloading liquid hydrogen flow of the target liquid hydrogen tanker 10 to achieve cooling buffering.

[0038] In this embodiment, the gas-liquid separation and reflux assembly 300 includes: The gas-liquid separator 310 uses gravity and centrifugal force to separate liquid hydrogen and gas in a liquefied and recovered two-phase flow, thereby obtaining the corresponding recovered liquid hydrogen and reflux tail gas.

[0039] Liquid phase pipeline 320: The separated recovered liquid hydrogen (>95% recovery rate) is directly transported back to the station's storage tank to complete product recovery.

[0040] Gas phase reflux line 330: The separated reflux tail gas (hydrogen, temperature ~21K) is led back to the cold side inlet of the cold buffer heat exchanger 210.

[0041] As one possible implementation, the gas phase reflux line 330 is connected to the cold energy buffer heat exchanger 210 or the main heat exchanger 220. When the gas phase reflux pipeline 330 is connected to the cold energy buffer heat exchanger 210, the reflux tail gas exchanges heat with the main unloading liquid hydrogen flow to stabilize the main unloading liquid hydrogen flow. When the gas phase return pipeline 330 is connected to the main heat exchanger 220, the main heat exchanger 220 is connected to the BOG collection tank 110, the cooler 130, the liquefaction heat exchanger 230 and the gas-liquid separator 310. The return tail gas is used as an auxiliary cold source to exchange heat with the pressurized cooling gas. After being heated, it returns to the BOG collection tank 110. This scheme can further extract the remaining cold energy of the return tail gas, form an internal cold energy cycle, and achieve almost zero emissions.

[0042] As an example, the workflow of a BOG recovery and reliquefaction unit in a practical application is as follows: BOG recovery start-up: Liquid hydrogen tanker 10 enters the station, the unloading pump is started, and liquid hydrogen enters the BOG recovery and reliquefaction unit through the unloading pipeline at a flow rate of 3000 kg / h. At the same time, the BOG released from the tanker and storage tank pressure (initial production rate of about 30 kg / h) is collected and pressurized.

[0043] Cold energy cascade utilization process: Liquid hydrogen (20K) first enters the cold buffer heat exchanger 210, where it exchanges heat with the low-temperature tail gas (22K) returning from the gas-liquid separator 310. The liquid hydrogen is gently reheated to 21.5K, and the flow state tends to stabilize.

[0044] Liquid hydrogen (21.5 K) enters the cold side of the main heat exchanger 220. Simultaneously, pressurized cooling gas, cooled to 300 K by aftercooler 130, enters its hot side. The two exchange heat counter-currently, with the pressurized cooling gas being deeply pre-cooled to 29 K (releasing most of the sensible heat and some of the latent heat). The liquid hydrogen, heated to 24.5 K, then enters the storage tank. This process handles approximately 70-80% of the total liquefaction cooling load.

[0045] It enters the liquefaction heat exchanger 230 through the main heat exchanger 220 (29K), exchanges heat with the 18K cold head provided by the helium refrigerator, and is finally cooled to 19K and completely liquefied, forming a liquefaction recovery two-phase flow.

[0046] The liquefied two-phase flow enters the cryogenic gas-liquid separator 310. Approximately 96-98% of the liquid hydrogen is recovered and returned to the storage tank. The remaining cryogenic reflux tail gas (21K) is guided back to the cold buffer heat exchanger 210, where it exchanges heat with the liquid hydrogen before returning to the BOG collection tank 110.

[0047] In summary, the design of the cascaded cold energy recovery heat exchanger group 200 in this embodiment can use the inherent cold energy of the unloaded liquid hydrogen flow as the main cold source for processing its own BOG, undertaking 60-80% of the liquefaction load, reducing the power demand of the external chiller by 50%-70%, and reducing the overall energy consumption of the system by 20%-35% compared with the traditional reliquefaction scheme, fundamentally solving the contradiction between high recovery rate and high energy consumption.

[0048] Example 2: Based on Example 1, a combustion power generation module 400 is added; all other aspects are the same as in Example 1. The gas phase reflux pipeline 330 can also be connected to the combustion power generation module 400; When the gas phase return pipeline 330 is connected to the combustion power generation module 400, the return exhaust gas is delivered to the combustion power generation module 400 to generate electricity; Furthermore, in this scheme, the BOG collection tank 110 is also connected to the combustion power generation module 400. When the amount of return exhaust gas is small (such as during system startup, low load or maintenance), the evaporated gas in the BOG collection tank 110 is used as an auxiliary power generation source. At this time, the return exhaust gas and / or the evaporated gas output from the BOG collection tank 110 are used to generate electricity through the combustion power generation module 400. Reference Figure 2 The combustion power generation module 400 includes a reheater and a hydrogen fuel cell. The evaporated gas output from the return tail gas and the BOG collection tank 110 is reheated by the reheater (heated to 60-80°C) and then transported to the hydrogen fuel cell to undergo an electrochemical reaction and directly generate direct current.

[0049] The hydrogen fuel cell is a proton exchange membrane fuel cell (PEMFC), which features fast start-up, high efficiency, matching requirements for hydrogen purity with the purity of reflux exhaust gas and evaporated gas, and flexible power range.

[0050] Note that the hydrogen fuel cell reaction generates a large amount of low-grade heat (approximately 60-80°C cooling water), which can be further recovered and utilized by the ORC module or the on-site hot water system.

[0051] Those skilled in the art can switch the connection scheme of the gas phase return pipeline 330 according to the actual situation, that is, control the gas phase return pipeline 330 to be connected to the cold energy buffer heat exchanger 210, the main heat exchanger 220 or the combustion power generation module 400, so as to make full use of the return tail gas.

[0052] As one possible implementation, it also includes a waste heat recovery module 500, which is used to recover waste heat emitted from the BOG recovery and reliquefaction unit and generate electricity.

[0053] The recovered waste heat includes: The compressor 120 of the refrigeration unit cools waste heat: When the refrigeration unit is running, its compressor 120 outlet will produce medium-temperature (usually 60-90℃) hot oil or hot water.

[0054] BOG handles the interstage cooling and aftercooling waste heat of the compressor 120 of the BOG processing unit 100.

[0055] Waste heat from the cooling cycle of hydrogen fuel cells.

[0056] In this embodiment, the waste heat recovery module 500 adopts an organic Rankine cycle system, which consists of an evaporator, a turbo expander, a generator, a condenser, and a working fluid pump. It selects an organic working fluid with a low boiling point and environmentally friendly properties (such as R245fa and R1233zd).

[0057] The heat transfer medium (hot water or hot oil) of each heat source (each compressor 120 and hydrogen fuel cell) transfers heat to the organic working fluid in the ORC evaporator, causing it to evaporate into high-pressure steam.

[0058] High-pressure organic working fluid steam drives the turbine expander to rotate, which in turn drives the generator to generate electricity.

[0059] After performing work, the low-pressure steam is cooled in the condenser (usually using ambient air or cooling water) and reliquefied, then pumped back to the evaporator by the working fluid pump to complete the cycle.

[0060] This embodiment breaks through the traditional single energy (cold energy) recovery mode by designing the waste heat recovery module 500. Through energy cascade utilization and multi-energy flow synergy, it recovers low-grade energy such as heat energy and residual pressure energy that might otherwise be wasted in the device and converts them into high-value electrical energy. Ultimately, it achieves closed-loop optimization of the "cold-electricity-hydrogen" energy flow and further improves the overall energy efficiency of the device.

[0061] Example 3: A control method for a BOG recovery and reliquefaction device, used for adaptive control of the BOG recovery and reliquefaction device based on the operating condition data of the BOG recovery and reliquefaction device described in Example 1. Reference Figure 3 This includes the following steps: S100: Collect operating data of the BOG recovery and reliquefaction unit; The operating condition data includes: Process parameters: inlet and outlet temperatures, pressures, and flow rates of each stage of heat exchangers; liquid hydrogen flow rate, BOG flow rate, and liquid hydrogen storage tank level and pressure.

[0062] Equipment status parameters: speed, power, current, vibration, noise, and bearing temperature of compressor 120 and refrigeration unit; opening degree of key valves.

[0063] Environmental parameters: ambient temperature and humidity.

[0064] Those skilled in the art can set the required operating data according to actual needs.

[0065] S200. Based on the operating condition data, perform dynamic process prediction to obtain the corresponding prediction results; The prediction results include BOG liquefaction rate, BOG temperature at the outlet of the main heat exchanger 220, and unit cooling load balance. In this embodiment, based on a preset dynamic process model, the state of the BOG recycling and reliquefaction device is simulated in real time based on the currently collected operating data, and the changes in the operating data are predicted, such as predicting the changing trend of key parameters in the next 15-30 minutes. The dynamic process model is a nonlinear dynamic mechanism model corresponding to the BOG recovery and reliquefaction device, which is established in advance based on the laws of conservation of mass, energy, and momentum, combined with a database of real physical properties of hydrogen at deep cryogenic temperatures (20K-300K). It serves as the core prediction engine of model predictive control (MPC).

[0066] The core state variables of the dynamic process model include the fluid temperature distribution, pressure, and gas-liquid phase content in each stage of the heat exchanger; the pressure in the BOG collection tank 110; and the liquid level in the liquid hydrogen storage tank 20.

[0067] In this embodiment, the inputs to the dynamic process model include: the measured instantaneous flow rate of liquid hydrogen unloading (the core disturbance source), BOG yield, ambient temperature, and control variables such as compressor speed of 120, chiller power, and opening degree of each regulating valve. Among these, given the BOG flow rate, liquid hydrogen flow rate, and liquid hydrogen storage tank level of 20, those skilled in the art can easily calculate the corresponding BOG yield based on existing technology, so it will not be described in detail.

[0068] In this embodiment, the output of the dynamic process model includes: BOG liquefaction rate at a preset time point (within 15-30 minutes), BOG temperature at the outlet of the main heat exchanger 220, and the unit's cold load balance.

[0069] S300. Evaluate the health index of each key device in the BOG recycling and reliquefaction unit based on the operating condition data. The key equipment is compressor 120 and refrigeration unit (such as BOG oil-free compressor 120 and helium refrigeration unit). In this embodiment, a corresponding equipment health model is pre-built for each key piece of equipment. The equipment health model includes a health analysis model, which is used to extract the current feature parameters corresponding to each evaluation feature based on the operating condition data. The input to the health analysis model is the equipment status parameters corresponding to the key equipment, that is, multi-source data based on vibration sensors (triaxial acceleration), acoustic sensors (microphone array), current harmonics, voltage harmonics, and process parameters (such as the inlet and outlet pressure difference and efficiency of compressor 120).

[0070] The output of the health analysis model is the current feature parameter corresponding to each evaluation feature. In this embodiment, historical normal operation data is used in advance to establish a benchmark health feature library for each state parameter of the device through machine learning algorithms (such as deep convolutional neural networks or support vector machines). This library includes benchmark feature parameters corresponding to several evaluation features. In practical applications, the current feature parameters corresponding to key devices are obtained based on the health analysis model, the deviation between the current feature parameters and the benchmark feature parameters is calculated in real time, and the health index of the key devices is obtained by weighted calculation based on the deviation of each evaluation feature. For example, the evaluation characteristics of compressor 120 include the fundamental frequency, harmonic amplitude, and sideband characteristics of the vibration spectrum. Combined with pre-obtained benchmark characteristic parameters, the corresponding health index HI is calculated based on the following formula: ; in: w i The weight of the i-th evaluation feature; The current feature parameter for the i-th evaluated feature; represents the baseline feature parameter for the i-th evaluation feature.

[0071] As an example, HI decreases linearly from 100% (new) and triggers an alert when it falls below a preset alert threshold (such as 75%).

[0072] As one possible implementation method, the device health model also includes an intelligent diagnostic model; The inputs to the intelligent diagnostic model and the health analysis model are the equipment status parameters corresponding to the key equipment, that is, multi-source data based on vibration sensors (triaxial acceleration), acoustic sensors (microphone array), current harmonics, voltage harmonics, and process parameters (such as the inlet and outlet pressure difference and efficiency of compressor 120).

[0073] The output of the intelligent diagnostic model is the fault identification result. In this embodiment, based on historical fault data, a device degradation model and fault feature library are established in advance using machine learning algorithms (such as deep learning and support vector machines). For example, by analyzing the changes in the vibration spectrum of compressor 120, early signs of blade imbalance or bearing wear can be identified in advance. Those skilled in the art can use existing fault detection technologies, so they will not be described in detail here.

[0074] Those skilled in the art can set the working order of the intelligent diagnostic model and the health analysis model according to actual needs. For example, the intelligent diagnostic model and the health analysis model can work simultaneously to output fault detection results and health index. Alternatively, the health analysis model can be run first, and the intelligent diagnostic model can be used to perform fault detection when the health index is lower than the preset warning threshold. This specification does not limit the specific steps involved.

[0075] S400. Based on the obtained prediction results and the health index of each key device, calculate the execution parameters of the BOG recycling and reliquefaction unit when the overall cost is minimized. The overall cost includes energy consumption cost and virtual equipment maintenance cost; The execution parameters include: The compressor 120 inverter setting frequency is used to adjust the compressor 120 speed to maintain stable BOG collection line pressure; The opening degree of the expansion valve of the helium refrigerator is used to control the final liquefaction unit outlet temperature; The opening degree of the liquid hydrogen bypass regulating valve of the main heat exchanger 220 is used to control the cooling capacity supply to the secondary heat exchanger. It also includes the cold energy access rate of the phase change energy storage module.

[0076] In this embodiment, the function for calculating the overall cost is: J = α * Energy consumption cost + β * Virtual equipment maintenance cost + γ * Recovery rate deviation penalty + δ * Control quantity change penalty.

[0077] in: J represents the total cost; Energy consumption cost: The energy consumption cost is calculated based on the power consumption of the chiller and compressor 120 and the corresponding time-of-use electricity price; Virtual maintenance cost: Calculated based on the preset reference maintenance cost and health index HI of each key device. The virtual maintenance cost is negatively correlated with the health index HI. The lower the HI, the higher this cost, which drives the system to protect the device.

[0078] Recovery rate deviation penalty, i.e., recovery rate setpoint - predicted recovery rate, is used to ensure that the BOG recovery rate is always not lower than the design target of 95%.

[0079] Control quantity change penalty: used to smooth the operation of compressor speed 120, valve opening, etc., to avoid frequent operation. Those skilled in the art can set this penalty based on existing technology according to actual needs.

[0080] The weight α is the energy consumption cost weight, which can be set by those skilled in the art according to actual needs; The weight β is a virtual maintenance cost weight, which can be set by those skilled in the art according to the importance of the critical equipment: for core equipment with serious consequences and high maintenance costs (such as helium refrigerators), a higher β value is assigned. For example, compressor 120 β = 0.8~1.5, and refrigerator β = 1.0~2.0.

[0081] The weight γ represents the penalty weight for recovery rate deviation. In optimization algorithms, a recovery rate ≥95% could be considered a hard constraint. However, including it as a penalty term with a larger weight in the objective function makes the solution more stable. The value of γ is typically 1-2 orders of magnitude larger than α and β. It is determined using a trial-and-error method and simulation verification, and simulation tests are conducted using digital twin models (dynamic process model and equipment health model). Given typical disturbances, γ is gradually increased until the deviation of the predicted recovery rate Rpred can be controlled within an acceptable range (e.g., ±0.5%) under various worst-case conditions. The typical value range is γ = 50~200.

[0082] The weight δ, representing the penalty weight for changes in the control quantity, is determined using a relative magnitude method. The value of δ must ensure that the penalty item is numerically on the same order of magnitude as other cost items (such as...), typically between 0.1 and 1.0. Different δ values ​​are set for different actuators. For example, a smaller δ (e.g., 0.1) is set for the liquid hydrogen main bypass valve, which has high inertia and slow action, to allow for necessary large adjustments; a larger δ (e.g., 1.0) is set for the compressor 120 frequency converter, which has a fast response and its lifespan is affected by frequent actions, to smooth its speed commands.

[0083] Constraints include BOG recovery rate ≥ 95%, upper and lower safety limits for equipment operating parameters (pressure, temperature, speed), and process dynamic equations described by a digital twin model.

[0084] In this embodiment, a digital twin model (dynamic process model and equipment health model) is used to simulate various typical operating conditions (such as unloading start-up, flow rate jump, and slight equipment degradation). A multi-objective optimization algorithm (such as NSGA-II) or an experience-based trial-and-error method is employed to find a set of weighting coefficients that achieve the optimal balance among various performance indicators (total energy consumption, equipment stress, recovery rate stability, and control smoothness). As a benchmark value.

[0085] Given a fixed weighting coefficient, the optimal control command sequence for the next time domain is obtained, including: setting the frequency of the BOG compressor 120 inverter, setting the opening of the expansion valve of the helium refrigerator, setting the opening of the liquid hydrogen bypass regulating valve of the secondary heat exchanger, setting the cold energy access rate of the phase change energy storage module, etc., and then sending the first command to the edge layer.

[0086] As one possible implementation method, several operating strategies are pre-defined, and a set of corresponding weight coefficients are set for each operating strategy; Economic model: High α, Medium β, High γ, Medium δ. Suitable for peak or stable electricity price periods.

[0087] Performance modes: Low α, Low β, High γ, Low δ. Suitable for handling severe disturbances and seeking rapid recovery.

[0088] Protection modes: α (Medium), β (High), γ (High), δ (High). Automatically switches modes when the device's health index decreases.

[0089] Note that the above high, medium, and low are comparison results relative to the adjustment range of this parameter. Those skilled in the art can adjust the weight coefficient of the above benchmark based on the above operating strategy.

[0090] For example, based on operational strategy settings, α can be set to 1.0–2.0 in economic mode and 0.2–0.5 in performance mode (e.g., ensuring rapid response to unloading disturbances). Simultaneously, α can be linked to time-of-use pricing signals. During high-price periods, α automatically increases (e.g., from 1.0 to 1.8) to enhance energy conservation; during low-price periods, α decreases (e.g., to 0.5), allowing the system to use more energy to improve performance or protect equipment.

[0091] When the device HI is lower than the warning threshold (e.g., 80%), it enters the forced entry protection model. At this time, the β value is increased (e.g., by 50%) to pursue stability. In actual use, during device startup, shutdown, or large disturbances, δ can be temporarily reduced based on the corresponding range to allow rapid changes in the control quantity to quickly stabilize the system. During steady-state operation, a larger δ is restored based on the corresponding range to pursue stability.

[0092] As one possible approach, machine learning can be used to analyze the relationship between optimal weights and performance results under different operating conditions, gradually establishing fuzzy rules or a small prediction model to achieve online small-scale adaptive fine-tuning of weights.

[0093] As one possible implementation method, specifically: When a start / stop signal from the unloading pump is detected or a step change exceeding a set threshold is observed in the liquid hydrogen flow meter, the dynamic process model is invoked. Based on the prediction results of the dynamic process model, feedforward compensation control commands are generated and issued in advance, including the following steps: Feedforward control: When the edge layer detects a start / stop signal from the unloading pump or a step change in the liquid hydrogen flow meter exceeding a set threshold, the dynamic process model is invoked to simulate the impact of the disturbance on future cooling loads.

[0094] Compensation command generation: Based on the prediction results of the dynamic process model, when a shortage or excess of cooling load is detected, a corresponding feedforward compensation control command is generated. For example, when the flow rate suddenly increases (the cooling source increases), the opening of the liquid hydrogen bypass valve is increased to increase the cooling capacity supply of the main heat exchanger 220, and the chiller power is simultaneously slightly reduced to save energy; if the flow rate suddenly decreases, the command is reversed. This "predictive" adjustment cannot be achieved in traditional PID feedback control (which only responds after the disturbance occurs); this embodiment generates the feedforward compensation control command in advance (e.g., 10-30 seconds) based on the prediction results.

[0095] Feedback correction: The control commands are corrected online by combining the deviation between real-time measured values ​​(such as the BOG temperature at the outlet of the main heat exchanger 220) and the predicted values ​​of the dynamic process model.

[0096] In this embodiment, the instantaneous flow rate of liquid hydrogen unloading is used as the core feedforward perturbation input.

[0097] As one possible implementation, when the HI assessed by the device health model remains below the warning threshold (e.g., the duration below the warning threshold exceeds a preset timeout period), a self-healing control step is also included: That is, under the constraint of ensuring the overall recovery rate, the optimization is carried out in the digital twin through simulation, and a protective operating condition adjustment scheme is generated and executed. The specific steps are as follows: A. Main equipment load reduction: Instruct the BOG compressor 120 to reduce its speed by the first preset value (5-10%) to reduce its mechanical stress.

[0098] B. Auxiliary equipment compensation: Synchronous command increases the power of the helium refrigerator by a second preset value (8-12%) to compensate for insufficient BOG precooling that may be caused by a decrease in the flow rate of compressor 120.

[0099] C. System coordination: Based on preset adjustment values, the bypass valves of each stage of heat exchanger are finely adjusted to redistribute the cold energy flow path.

[0100] This process transforms post-failure shutdown maintenance into pre-failure dynamic intervention and load redistribution, extending equipment lifespan while maintaining production.

[0101] As one possible implementation method, prediction-based energy efficiency scheduling: External information access: The system accesses weather forecasts (ambient temperature for the next 24-72 hours), time-of-use electricity pricing tables, and future liquid hydrogen unloading / refueling plans.

[0102] Proactive optimization: Optimizing system operation strategies on longer time scales (e.g., hours). For example: During nighttime hours when ambient temperatures are low and electricity prices are low, the command system appropriately increases the operating baseline load, utilizing liquid hydrogen cold energy and low-cost electricity to liquefy and store more BOG.

[0103] During peak electricity price periods or when ambient temperature is high, the phase change energy storage module's cooling capacity is prioritized, provided that the basic recovery rate is met, and the cooling-electricity co-generation unit is instructed to generate more electricity to reduce the need for purchasing high-priced electricity from outside sources.

[0104] S500: Control the operation of the BOG recycling and reliquefaction device based on the obtained execution parameters and continuously monitor the execution effect.

[0105] Example 4: Control method for BOG recycling and reliquefaction device. Based on Example 3, a power generation revenue term is introduced to adaptively control the BOG recycling and reliquefaction device based on the operating data of the BOG recycling and reliquefaction device described in Example 2. The solution result also includes control commands for hydrogen fuel cells. In this embodiment, the collected operating data also includes the real-time power generation and equipment efficiency of the hydrogen fuel cell and waste heat recovery module 500 (ORC turbine equipment), enabling more accurate global status perception and decision-making. Those skilled in the art can configure it according to actual needs. In this embodiment, the key equipment also includes a hydrogen fuel cell and a waste heat recovery module 500 (ORC turbine equipment), that is, calculating the health index of the hydrogen fuel cell and the waste heat recovery module 500 and performing preventive maintenance scheduling for them.

[0106] In this embodiment, based on the obtained prediction results and the health index of each key device, the execution parameters of the BOG recycling and reliquefaction device are calculated to minimize the overall cost. In this embodiment, the key equipment also includes a hydrogen fuel cell and waste heat recovery module 500 (ORC turbine equipment), that is, calculating the health index of the hydrogen fuel cell and waste heat recovery module 500; In this embodiment, based on the obtained prediction results and the health index of each key device, the execution parameters of the BOG recycling and reliquefaction device are calculated to minimize the overall cost; the execution parameters also include the start-up commands of the hydrogen fuel cell and the waste heat recovery module 500.

[0107] The function for calculating the overall cost in this embodiment is: J = α * energy consumption cost + β * virtual equipment maintenance cost + γ * (recovery rate deviation penalty) + δ * control quantity change penalty + ζ power generation revenue item; The revenue from electricity generation is calculated as: cost of electricity purchase minus revenue from electricity generation. The weight ζ is set in the same way as above; By introducing a power generation revenue term, a dynamic trade-off is made between using more electricity to increase BOG liquefaction rate and using less electricity or even generating electricity to earn revenue, in order to find the global optimum.

[0108] During peak electricity price periods, the intelligent control unit will instruct the hydrogen fuel cell module to start first and increase the load of the ORC module as much as possible to maximize self-generation and self-consumption and reduce the need to purchase electricity at high prices. During off-peak electricity prices at night or when BOG production is low, the fuel cell may be instructed to reduce its load or shut down to store or liquefy the limited high-value hydrogen while operating on cheaper grid electricity.

[0109] Example 5: A control system for a BOG recycling and reliquefaction unit, used for adaptive control of the BOG recycling and reliquefaction unit based on the operating condition data of the BOG recycling and reliquefaction unit described in Examples 1 and 2, including: The execution perception module, located in the edge control layer, is used to collect the operating condition data of the BOG recycling and reliquefaction device, and also to control the operation of the BOG recycling and reliquefaction device based on the obtained execution parameters and continuously monitor the execution effect.

[0110] In practical use, it is deployed at the device site and is responsible for high-speed, deterministic real-time control and data acquisition.

[0111] In this embodiment, the execution perception module includes a multiphysics sensing network and an execution mechanism array; The physical field sensing network includes: Process parameter sensors: temperature (ultra-low temperature to ambient temperature), pressure, flow rate, liquid level, and hydrogen purity analyzer.

[0112] Equipment status sensors: Vibration, noise, and winding temperature sensors for critical equipment (such as BOG compressor 120, cryogenic pump, and refrigeration unit).

[0113] Environmental sensors: ambient temperature, humidity, and wind speed sensors.

[0114] Video and gas leak monitoring: infrared thermal imaging camera, multi-point hydrogen concentration detector.

[0115] The actuator array includes various pneumatic / electric regulating valves, shut-off valves, frequency converters (driving compressor 120, pumps), and refrigeration power controllers.

[0116] In practical applications, it can receive and execute optimized setpoints or control command sequences issued from the cloud optimization layer, and control the operation of the actuator array based on the classic PID control algorithm.

[0117] In practical applications, safety interlocking and emergency shutdown can be implemented: the preset safety logic is executed, and when overpressure, overtemperature, leakage or serious equipment failure is detected, the interlocking protection action is immediately triggered to ensure system safety.

[0118] Command reception and execution: Reliably receive and execute optimization settings or control command sequences issued from the cloud optimization layer.

[0119] The optimization control module, located in the cloud, is used to perform dynamic process prediction based on the operating condition data, obtain corresponding prediction results, and evaluate the health index of each key device in the BOG recycling and reliquefaction unit based on the operating condition data. It is also used to calculate the execution parameters of the BOG recycling and reliquefaction unit when the overall cost is minimized based on the obtained prediction results and the health index of each key device.

[0120] In practical applications, it is deployed on industrial cloud platforms or high-performance servers to run high-fidelity models, perform complex optimization calculations, and manage equipment health.

[0121] In this embodiment, the execution perception module located at the edge control layer and the optimization control module located in the cloud achieve bidirectional data synchronization and command issuance through a high-speed and secure industrial communication network (such as OPC UA over TSN), forming a closed-loop intelligent control circuit.

[0122] In this embodiment, the optimization control module includes a digital twin module and an optimization module; The digital twin module is used to perform simulation based on the operating data using a preset digital twin model to obtain prediction results and health indices of key equipment; based on the obtained prediction results and health indices of each key equipment, the execution parameters of the BOG recycling and reliquefaction unit are calculated to minimize the overall cost. The digital twin model in this embodiment includes: Dynamic process model: A high-fidelity mechanism model of the liquid hydrogen BOG reliquefaction system based on the conservation of mass, energy and momentum, which can simulate and predict the dynamic behavior of the system in real time for the next few minutes to hours.

[0123] Equipment Health Model: A key equipment health status assessment and life prediction model built based on multi-physical field data such as vibration and acoustics, using machine learning algorithms (such as deep learning), and outputting the health index (HI) of key equipment.

[0124] The optimization module is a model predictive control (MPC) and mixed integer programming (MIP) solver used to solve for minimizing the overall cost.

[0125] In this embodiment, the optimization module includes: Solving unit: Solve optimization problems with overall operating cost as the objective function in minute-level cycles, and dynamically output the optimal control instruction set.

[0126] Feedforward-feedback composite control unit: Utilizes a dynamic model to perform advance compensation (feedforward) for large disturbances such as the start / stop of unloading flow, and combines real-time feedback for fine-tuning.

[0127] Self-healing control unit: When the equipment health index is below the threshold, it automatically generates and executes "protective operating conditions", adjusts operating parameters to reduce equipment stress, and maintains system performance through compensation strategies.

[0128] Dispatch unit: Combines weather forecasts, electricity price signals, and unloading plans to conduct forward-looking energy and economic dispatch.

[0129] In summary, the control flow of the control system designed in this embodiment includes: Uplink data flow: Sensor data from the physical layer → Local layer acquisition and preprocessing → Uploaded via network to the digital twin module of the intelligent optimization layer, driving real-time synchronization and updating of the model.

[0130] Downlink control flow: The global optimization module of the intelligent optimization layer calculates the optimal instruction set → sends it to the basic controller of the local layer → the basic controller parses and drives the field actuators to perform actions.

[0131] Closed-loop optimization flow: The execution results are fed back to the digital twin through sensors and compared with the predicted values. The model deviations are used to correct the next round of optimization calculations, forming a continuous improvement closed loop of "perception-prediction-optimization-execution-feedback".

[0132] That is, the workflow of the system is as follows: Data uplink: The execution awareness module at the edge layer collects data in real time, cleans and packages it, and then uploads it to the cloud.

[0133] Twin synchronization and prediction: The cloud-based digital twin module receives data, drives the dynamic model to update its state, and predicts future operating conditions.

[0134] Health assessment: The equipment health model analyzes data in parallel and updates the health index of each device.

[0135] Optimization Solution: The global optimization module integrates real-time data, forecast information, health status, external plans, and price signals to solve the MPC optimization problem.

[0136] Instruction generation and distribution: Generate a comprehensive optimal instruction set that includes basic control, feedforward compensation, and self-healing adjustment, and distribute it to the edge layer.

[0137] Command execution and monitoring: The edge layer executes commands and continuously monitors the execution effect, forming a complete intelligent closed loop of "perception-decision-execution-evaluation".

[0138] As one possible implementation, it also includes a training module, which is used to mine historical operating data to achieve energy efficiency analysis, root cause diagnosis of faults, and periodically retrain and update the digital twin model with new data to maintain its prediction accuracy.

[0139] As one possible implementation, it also includes 5.1.35.1.2 Application and Cloud Platform Layer. It provides a centralized deployment, version management, and large-scale training environment for remote monitoring (HMI / Web), alarm management, report generation, carbon footprint accounting, and digital twin models and intelligent algorithms.

[0140] It supports centralized management and collaborative optimization across multiple sites, and provides a platform foundation for future data value-added services (such as predictive maintenance subscriptions).

[0141] Case Study: This case study uses a liquid hydrogen refueling station with a daily hydrogen refueling capacity of 1000 kg as the application scenario. The equipment parameters for the BOG recovery and reliquefaction unit are as follows: Cascaded cold energy recovery heat exchanger group 200: adopts aluminum multi-flow plate-fin heat exchanger. The second-stage main heat exchanger 220 is designed with a heat exchange area of ​​150㎡, a liquid hydrogen flow rate of 3000kg / h, and a BOG flow rate of 50kg / h.

[0142] Compressor 120: An oil-free screw compressor 120 is selected to compress BOG from 0.15MPaA to 2.0MPaA.

[0143] Refrigeration unit: Equipped with a small, high-efficiency helium Brayton cycle refrigeration unit with a rated power of 15kW.

[0144] Phase change energy storage module: The main heat exchanger 220 integrates a neon (Ne) PCM unit with a phase change temperature of approximately 27K.

[0145] Install a 5kW PEM fuel cell to process excess BOG; and set up an ORC unit to recover waste heat from the chiller.

[0146] After 72 hours of continuous operation testing, the key data are as follows: like Figure 4 As shown, the average recovery rate of BOG was 97.5% (with a peak of 99.1% at one point), consistently exceeding the design target of 95%.

[0147] System energy consumption: The total power consumption of the reliquefaction system is 28kW. Among them, the compressor 120 consumes 18kW and the chiller consumes 10kW. Compared with the traditional independent reliquefaction scheme (which requires about 45kW of chiller power + similar compressor power), the total energy consumption is reduced by about 30-40%.

[0148] Operational stability: Under the disturbance of a step change in unloading flow rate from 3000kg / h to 2000kg / h, the maximum fluctuation of key parameters (such as the BOG outlet temperature of the secondary heat exchanger) is less than ±1.5K, which is 65~80% less than the fluctuation of traditional PID control (which can reach more than ±5K).

[0149] As shown above, the design of the control system enables proactive compensation and multi-objective dynamic optimization for strong disturbances such as sudden changes in unloading flow. While ensuring a BOG recovery rate of ≥95%, it significantly improves system reliability and overall lifecycle economics.

[0150] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0151] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0152] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied 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.

[0153] This invention is described with reference to flowchart illustrations and / or block diagrams of the method, terminal device (system), and computer program product according to the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0154] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0155] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal equipment, causing a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0156] It should be noted that: The phrase "an embodiment" or "an embodiment" used in this specification means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. Therefore, the phrase "an embodiment" or "an embodiment" appearing in various places throughout the specification does not necessarily refer to the same embodiment.

[0157] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0158] Furthermore, it should be noted that the shapes and names of the parts and components described in the specific embodiments described in this specification may differ. All equivalent or simple variations made to the structure, features, and principles described in this patent concept are included within the protection scope of this patent. Those skilled in the art to which this invention pertains may make various modifications or additions to the described specific embodiments or use similar methods to replace them, as long as they do not depart from the structure of this invention or exceed the scope defined in these claims, they should all fall within the protection scope of this invention.

Claims

1. A BOG recovery and reliquefaction device is used to recover and reliquefy the evaporated gas generated during the unloading and settling process of liquid hydrogen storage and transportation facilities, wherein the liquid hydrogen storage and transportation facilities include liquid hydrogen tank trucks and liquid hydrogen storage tanks. Its features are, include: The BOG processing unit, the cascaded cold energy recovery heat exchanger group, and the gas-liquid separation and reflux unit are connected in sequence. The BOG processing component is used to collect the vapors generated when the target liquid hydrogen tanker is unloaded, as well as the vapors generated when the liquid hydrogen storage tank is left to stand; it is also used to pressurize and cool the collected vapors, and then output the pressurized and cooled gas to the cascaded cold energy recovery heat exchanger group for cooling and liquefaction. The cascaded cold energy recovery heat exchanger assembly is used to exchange heat between the liquid hydrogen unloaded from the target liquid hydrogen tanker and the pressurized cooling gas, so that the pressurized cooling gas is liquefied and a liquefied recovery two-phase flow is generated. The gas-liquid separation and reflux assembly is used to separate the liquefied two-phase flow output from the liquefied heat exchanger into gas and liquid, obtain corresponding recovered liquid hydrogen and reflux tail gas, transport the recovered liquid hydrogen to the corresponding liquid hydrogen storage tank, and transport the reflux tail gas to the BOG processing assembly.

2. The BOG recovery and reliquefaction device according to claim 1, characterized in that: The cascaded cold energy recovery heat exchanger group includes a refrigeration unit, and also includes a cold energy buffer heat exchanger, a main heat exchanger and a liquefaction heat exchanger cascaded in sequence, wherein the liquefaction heat exchanger is coupled to the cold head of the refrigeration unit. The cold energy buffer heat exchanger is connected to the gas-liquid separation and reflux assembly, the BOG processing assembly and the target liquid hydrogen tanker respectively, and is used to exchange heat between the main unloading liquid hydrogen flow from the target liquid hydrogen tanker and the reflux exhaust gas from the gas-liquid separation and reflux assembly, and to transport the heat-exchanged main unloading liquid hydrogen flow to the main heat exchanger, and to transport the heat-exchanged reflux exhaust gas to the BOG processing assembly. The main heat exchanger is also connected to the BOG processing assembly and the liquid hydrogen storage tank, and is used to pre-cool the pressurized cooling gas by utilizing the cold energy of the main unloading liquid hydrogen flow. The main unloading liquid hydrogen flow after heat exchange enters the liquid hydrogen storage tank. The liquefaction heat exchanger is used to further cool the pressurized cooling gas pre-cooled by the main heat exchanger using the refrigerator, so that it is completely liquefied and outputs a liquefied recovery two-phase flow.

3. The BOG recovery and reliquefaction device according to claim 2, characterized in that: The main heat exchanger is equipped with a phase change energy storage buffer module, which encapsulates a phase change material with a phase change temperature of 25K-30K.

4. The BOG recovery and reliquefaction device according to claim 2, characterized in that, The gas-liquid separation and reflux assembly includes: A gas-liquid separator is used to separate liquid hydrogen and gas in a liquefied and recovered two-phase flow by using gravity and centrifugal force, to obtain the corresponding recovered liquid hydrogen and reflux tail gas. The liquid phase pipeline is used to directly transport the separated recovered liquid hydrogen back to the storage tank in the station to complete the product recovery. The gas phase reflux pipeline is used to guide the separated reflux tail gas back to the cold energy buffer heat exchanger, and then enter the BOG processing unit through the cold energy buffer heat exchanger.

5. The BOG recovery and reliquefaction device according to claim 4, characterized in that, It also includes combustion power generation modules; The gas phase reflux pipeline is connected to the cold energy buffer heat exchanger or the combustion power generation module; When the gas phase reflux pipeline is connected to the combustion power generation module, the reflux exhaust gas is delivered to the combustion power generation module for power generation.

6. The control method for the BOG recovery and reliquefaction device as described in any one of claims 1 to 5, characterized in that, Includes the following steps; Collect operating data from the BOG recovery and reliquefaction unit; Based on a preset dynamic process model, the state of the BOG recovery and reliquefaction device is simulated in real time based on the currently collected operating data, and the changes in the operating data are predicted to obtain the corresponding prediction results. The health index of each key piece of equipment in the BOG recovery and reliquefaction unit is evaluated based on the operating data. Based on the obtained prediction results and the health index of each key device, the execution parameters of the BOG recycling and reliquefaction unit are calculated to minimize the overall cost. The BOG recycling and reliquefaction device is controlled based on the obtained execution parameters, and the execution effect is continuously monitored.

7. The control method for the BOG recovery and reliquefaction device according to claim 6, characterized in that: A corresponding health analysis model is pre-built for each key piece of equipment. The health analysis model is used to extract the current feature parameters corresponding to each evaluation feature based on the operating condition data. Determine the baseline characteristic parameters corresponding to each evaluation characteristic; The deviation between the current feature parameters and the benchmark feature parameters is calculated in real time. The health index of the key equipment is obtained by weighting the deviation of each evaluation feature. The calculation formula is as follows: ； in: w i The weight of the i-th evaluation feature; The current feature parameter for the i-th evaluated feature; represents the baseline feature parameter for the i-th evaluation feature.

8. The control method for the BOG recovery and reliquefaction device according to claim 6, characterized in that: The comprehensive cost is calculated based on energy consumption cost, virtual equipment maintenance cost, and recovery rate deviation penalty. The energy consumption cost is calculated based on the power consumption of the chiller and compressor and the corresponding time-of-use electricity price; The virtual maintenance cost of each key piece of equipment is negatively correlated with the corresponding health index.

9. The control method for the BOG recovery and reliquefaction device according to claim 6, characterized in that, When a start / stop signal of the unloading pump is detected or a step change in the liquid hydrogen flow meter exceeds the set threshold, the dynamic process model is invoked. Based on the prediction results of the dynamic process model, a feedforward compensation control command is generated and issued.

10. The control system of the BOG recovery and reliquefaction apparatus as described in any one of claims 1 to 5, characterized in that, include; The execution perception module, located in the edge control layer, is used to collect the operating condition data of the BOG recycling and reliquefaction device, and also to control the operation of the BOG recycling and reliquefaction device based on the obtained execution parameters and continuously monitor the execution effect. Optimization control module: Located in the cloud, it is used to simulate the state of the BOG recycling and reliquefaction device in real time based on the preset dynamic process model and the currently collected operating data, and to predict the changes in the operating data to obtain the corresponding prediction results. It is also used to evaluate the health index of each key device in the BOG recycling and reliquefaction unit based on the operating condition data; and to calculate the execution parameters of the BOG recycling and reliquefaction unit when the overall cost is minimized based on the obtained prediction results and the health index of each key device.

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