System and method for managing an ammonia cracking plant

Abstract

To provide a system for guaranteeing a stable operation of an ammonia decomposition plant under an emergency condition, and to provide a method therefor.SOLUTION: A system according to the present disclosure comprises: a model-producing module for producing a digital twin model including a replica model of a physical constituent element of an ammonia decomposition plant; an input module for inputting a kinetic energy request amount and output information of an ammonia decomposition device included in the ammonia decomposition plant into the digital twin model; an emergency condition imposition module for imposing an emergency condition on the replica model of the physical constituent element with respect to a preset emergency scenario; a data collection comparison module for comparing first data when the emergency condition is imposed with second data when no emergency condition is imposed, by collecting data from the digital twin model under the imposed emergency condition; and a scenario-producing module for producing a control scenario for the preset emergency scenario based on a result of comparing the first data with the second data.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to systems and methods for managing an ammonia cracking plant. [Background technology]

[0002] In recent years, as various environmental issues have emerged as major global problems, there has been a growing demand for the introduction of environmentally friendly alternative energy sources to replace existing internal combustion engines, not only in general vehicles but also in heavy machinery such as excavators. As a result, fuel cell systems that use fuel cells (FCs) as a power source have been attracting attention as an environmentally friendly alternative energy source.

[0003] To ensure smooth operation and high performance of a fuel cell system, the role of the Energy Management System (EMS) is important as it determines how to distribute power demand among power sources appropriately, and this requires stable and reliable EMS operation.

[0004] In a situation where there are multiple pipes, when the flow rate is concentrated in a specific pipe, it is necessary to equalize the flow rate by automatically reducing the flow rate of that pipe. Existing methods have difficulty accounting for the complex interactions between different components of the system. To solve this problem, research is being conducted on Digital Twin (DT), which provides an accurate real-time simulation of the entire physical system. Summary of the Invention [Problem to be solved by the invention]

[0005] According to one aspect of the present disclosure, a system and method for ensuring stable operation of an ammonia decomposition plant under emergency conditions can be provided. [Means for solving the problem]

[0006] A system according to one embodiment of the present disclosure may include a model generation module that generates a digital twin model including a replica model of physical components of an ammonia cracking plant; an input module that inputs dynamic energy demand and output information of an ammonia cracker included in the ammonia cracking plant into the digital twin model; an emergency condition imposition module that imposes emergency conditions on the replica model of the physical components for a preset emergency scenario; a data collection and comparison module that collects data from the digital twin model under the imposed emergency condition and compares first data when the emergency condition is imposed with second data when the emergency condition is not imposed; and a scenario generation module that generates a control scenario for the preset emergency scenario based on a comparison result of the first data and the second data.

[0007] According to one embodiment, the physical components of the ammonia cracking plant include the ammonia cracker, sensors, and controllers, and the model generation module can update the digital twin model with real-time data from the ammonia cracking plant.

[0008] According to one embodiment, the input module can compare the difference between the dynamic energy demand actually required by the digital twin model and the output of the output information of the ammonia cracking plant.

[0009] According to one embodiment, the emergency condition imposition module can set multiple virtual emergencies in the digital twin model to prepare for potential emergencies, evaluate the response and performance of the digital twin model in the set virtual emergencies, and predict adjustments necessary to ensure the safety and stability of the ammonia cracking plant.

[0010] According to one embodiment, the data collection and comparison module can identify weaknesses in the system that may occur in each emergency and the degree of vulnerability for each replication model based on the data.

[0011] According to one embodiment, the scenario generation module may use the comparison data between the first data and the second data to generate a control scenario for a potential emergency situation.

[0012] According to one embodiment, the digital twin model may include a plant control unit corresponding to a replica model of the control device that controls the ammonia decomposition device, and a data collection unit that collects the real-time data.

[0013] According to one embodiment, the physical components of the ammonia decomposition plant may further include a feed blower, a flow control valve, and at least one reaction unit, and the sensors may include a temperature sensor and a pressure sensor.

[0014] According to one embodiment, the at least one reaction unit may include a plurality of reaction sections that receive a flow rate of a feed for a reforming reaction and a flow rate of a feed for a combustion reaction, and a combustion section that outputs a combustion flue gas.A method according to one embodiment of the present disclosure may include generating a digital twin model including a replica model of physical components of an ammonia cracking plant, inputting dynamic energy demand and output information of an ammonia cracker included in the ammonia cracking plant into the digital twin model, imposing an emergency condition on the replica model of the physical components for a preset emergency scenario, collecting data from the digital twin model under the imposed emergency condition, comparing first data when the emergency condition is imposed with second data when the emergency condition is not imposed, and generating a control scenario for the preset emergency scenario based on a comparison result between the first data and the second data. [Effects of the Invention]

[0015] According to one embodiment of the present disclosure, the stable operation of the ammonia decomposition plant is ensured under emergency conditions, thereby improving the reliability of the system.

[0016] Additionally, according to one embodiment of the present disclosure, by designing a digital twin model to closely mimic the operation of a plant under various conditions, real-time monitoring, analysis, and optimization effects are achieved.

[0017] Furthermore, according to an embodiment of the present disclosure, appropriate action scenarios to be implemented in response to specific emergency situations are pre-constructed, thereby ensuring the safety of the system.

[0018] Additionally, one embodiment of the present disclosure may help identify potential areas for improvement, ultimately contributing to the overall sustainability and cost-effectiveness of the plant. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram illustrating a system according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating the relationship between a plant and a digital twin model according to an embodiment of the present disclosure. [Figure 3] FIG. 3 is a diagram illustrating a method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, embodiments of the present invention will be described in more detail with reference to the drawings. However, these embodiments are merely illustrative of the present invention and are not intended to limit the present invention.

[0021] The same reference numerals refer to the same components throughout this disclosure. This disclosure does not describe all elements of the embodiments, and general content in the technical field to which the disclosure belongs or content that overlaps with the embodiments will be omitted. The terms "unit, module, component, block" used in this specification may be embodied in software or hardware, and depending on the embodiment, multiple "units, modules, components, blocks" may be embodied as one component, or one "unit, module, component, block" may include multiple components.

[0022] Throughout this specification, when a part is "coupled" to another part, it means not only a direct connection but also an indirect connection, including a connection via a wireless communication network.

[0023] Furthermore, unless otherwise specified, when a part "comprises" a certain component, it does not exclude other components, but means that it may further include other components.

[0024] Throughout this specification, a member being "on" another member includes not only when the member is in contact with the other member, but also when there is another member between the two members.

[0025] The terms "first," "second," etc. are used to distinguish one component from another, and are not intended to limit the components.

[0026] The singular expression includes the plural expression unless the context clearly indicates otherwise.

[0027] The identification numbers in each step are used for ease of description and do not dictate the order of the steps, and the steps may be performed in a manner other than the stated order unless the context clearly dictates a particular order.

[0028] In this specification, the term "device according to the present disclosure" includes all of various devices capable of performing computation and providing a result to a user. For example, the device according to the present disclosure may include all of a computer, a server device, and a portable terminal, and may take any form.

[0029] Here, the computer may include, for example, a notebook computer, a desktop computer, a laptop computer, a tablet PC, a slate PC, etc. equipped with a web browser.

[0030] The server device is a server that communicates with external devices and processes information, and may include an application server, a computing server, a database server, a file server, a game server, a mail server, a proxy server, a web server, and the like.

[0031] The portable terminal is, for example, a wireless communication device that ensures portability and mobility, and may include all kinds of handheld-based wireless communication devices such as PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), WiBro (Wireless Broadband Internet) terminals, and smartphones, as well as wearable devices such as watches, rings, bracelets, anklets, necklaces, glasses, contact lenses, or head-mounted devices (HMDs).

[0032] FIG. 1 is a diagram illustrating a system according to an embodiment of the present disclosure.

[0033] 1 , a system 100 can manage an ammonia cracking plant. The system 100 can include a physical plant 110, a model generation module 121, an input module 122, an emergency condition imposition module 123, a data collection and comparison module 124, a scenario generation module 125, and a digital twin model 130.

[0034] The physical plant 110 may be, but is not limited to, an ammonia decomposition plant. The physical plant 110 embodied as an ammonia decomposition plant may include an ammonia decomposition unit 111, a controller 112 that controls the ammonia decomposition unit 111, a feed blower 113, a flow control valve 114, a reaction unit 115, a temperature sensor 116, and a pressure sensor 117. The temperature sensor 116 or the pressure sensor 117 may be referred to as a sensor.

[0035] Model generation module 121 can generate digital twin model 130. Digital twin model 130 can include replica models of physical components of physical plant 110. The physical components of physical plant 110 can be, for example, physical components of an ammonia decomposition plant. In this case, the physical components of physical plant 110 can include an ammonia decomposition unit 111, a control device 112, a feed blower 113, a flow control valve 114, a reaction unit 115, a temperature sensor 116, and a pressure sensor 117. The replica models included in digital twin model 130 can include an ammonia decomposition unit 131, a control device 132, a feed blower 133, a flow control valve 134, a reaction unit 135, a temperature sensor 136, and a pressure sensor 137.

[0036] The model generation module 121 can continuously update the digital twin model 130 with real-time data from the ammonia cracking plant for more accurate and specific simulations and predictions.

[0037] The input module 122 can input the dynamic energy demand and output information of the physical plant 110 to the digital twin model 130. For example, the input module 122 can input the dynamic energy demand and output information of the ammonia cracker 111 included in the ammonia cracking plant to the digital twin model 130.

[0038] The input module 122 can compare the difference between the dynamic energy demands actually required by the digital twin model 130 and the output of the ammonia cracking plant power information.

[0039] Emergency condition imposition module 123 can impose emergency conditions on the replica models of the physical components of physical plant 110 for pre-defined emergency scenarios.

[0040] The emergency condition imposition module 123 can set a variety of virtual emergencies in the digital twin model 130 to prepare for potential emergency situations. The emergency condition imposition module 123 can then evaluate the response and performance of the digital twin model 130 in the set virtual emergencies. The emergency condition imposition module 123 can also predict adjustments necessary to ensure the safety and stability of the ammonia cracking plant.

[0041] The data collection and comparison module 124 can collect data from the digital twin model 130 under the imposed emergency condition. The data collection and comparison module 124 can then compare first data when the emergency condition is imposed with second data when the emergency condition is not imposed. Comparison data can be generated that includes the results of comparing the first data and the second data.

[0042] Based on the data, the data collection and comparison module 124 can identify weaknesses in the system 100 that may occur in each emergency situation and the degree of vulnerability for each replication model.

[0043] The scenario generation module 125 can generate a control scenario for a preset emergency scenario based on the comparison data.

[0044] The scenario generation module 125 can use the comparison data between the first data and the second data to generate control scenarios for a variety of potential emergency situations.

[0045] As described above, the present invention has the effect of improving the reliability of the system by ensuring stable operation of the ammonia decomposition plant under emergency conditions.

[0046] Also, as mentioned above, by designing a digital twin model to closely mimic the operation of a plant under a variety of conditions, real-time monitoring, analysis, and optimization effects can be achieved.

[0047] Furthermore, as described above, by constructing appropriate action scenarios to be implemented in response to specific emergency situations in advance, the safety of the system can be ensured.

[0048] Additionally, the foregoing has the effect of helping to identify potential areas for improvement, an effect that ultimately contributes to the overall sustainability and cost-effectiveness of the plant.

[0049] FIG. 2 is a diagram illustrating the relationship between a plant and a digital twin model according to an embodiment of the present disclosure.

[0050] Referring to FIG. 2, the relationship diagram 200 may include a dynamic load input 210, a digital twin model 220, first to Nth reaction units (230_1, 230_N), first and second blowers (241, 242), first to fourth control valves (251, 252, 253, 254), and first to tenth information (I1, I2, I3, I4, I5, I6, I7, I8, I9, I10).

[0051] The dynamic load input 210 may correspond to the dynamic energy demands discussed above. The dynamic load input 210 may be input into the digital twin model 220.

[0052] The digital twin model 220 may include a plant control unit 221 corresponding to a replica model of a control device that controls the ammonia cracker, and a data collection unit 222 that collects real-time data. The data collection unit 222 may receive a dynamic load input 210 and inputs of first through tenth information (I1, I2, I3, I4, I5, I6, I7, I8, I9, and I10). The data collection unit 222 may receive inputs of a feed flow rate for the reforming reaction and a feed flow rate for the combustion reaction, which are provided via first through fourth control valves (251, 252, 253, and 254).

[0053] The number of the first to Nth reaction units (230_1, 230_N) may be N, as shown in FIG. 2. N may be an integer equal to or greater than 2, but is not limited thereto. The first reaction unit (230_1) may include a first reaction section (231_1), a combustion section (232_1), and a second reaction section (233_1). The Nth reaction unit (230_N) may include a first reaction section (231_N), a combustion section (232_N), and a second reaction section (233_N). The reaction sections may receive a feed flow rate for a reforming reaction and a feed flow rate for a combustion reaction. The first reaction section (231_1) may receive a reforming reaction feed. The first reaction section (231_1) may output a ninth information (I9). The combustion section (232_1) may receive a combustion reaction feed. The combustion unit (232_1) may output combustion flue gas and tenth information (I10). The second reaction unit (233_1) may output sixth information (I6) and reforming reaction products. The first reaction unit (231_N) may output seventh information (I7). The combustion unit (232_N) may receive a combustion reaction feed. The combustion unit (232_N) may output combustion flue gas and eighth information (I8). The second reaction unit (233_N) may output fifth information (I5) and reforming reaction products.

[0054] The reforming reaction feed may be input to the first blower 241. The first blower 241 may provide the reforming reaction feed to the first and third control valves (251, 253). The combustion reaction feed may be input to the second blower 242. The combustion reaction feed may include fuel and air. The second blower 242 may provide the combustion reaction feed to the second and fourth control valves (252, 254).

[0055] 3 is a diagram illustrating a method according to an embodiment of the present disclosure. Referring to FIG. 3, a method according to an embodiment of the present disclosure can manage an ammonia cracking plant.

[0056] A step is performed of generating a digital twin model that includes replica models of the physical components of the ammonia cracking plant (S100).

[0057] Regarding step S100, for example, with reference to FIG. 1 , the model generation module 121 can generate a digital twin model 130 including replica models of the physical components of the physical plant 110 (e.g., ammonia cracker 131, controller 132, feed blower 133, flow control valve 134, reaction unit 135, temperature sensor 136, and pressure sensor 137, etc.), and continuously update the digital twin model 130 with real-time data from the ammonia cracking plant for more accurate and specific simulations and predictions.

[0058] A step of inputting dynamic energy demand and output information of an ammonia decomposition unit included in an ammonia decomposition plant into the digital twin model is performed (S200).

[0059] Regarding step S200, for example, referring to FIG. 1 , the input module 122 can input the dynamic energy demand into the digital twin model 130 and input the output information of the ammonia decomposition unit 111 included in the ammonia decomposition plant, and compare the difference between the dynamic energy demand actually required by the digital twin model 130 and the output amount of the output information of the ammonia decomposition plant.

[0060] A step of imposing an emergency condition on the replica model of the physical component for a preset emergency scenario is performed (S300).

[0061] 1, for example, the emergency condition imposition module 123 can set a variety of virtual emergencies in the digital twin model 130 to prepare for potential emergency situations. The emergency condition imposition module 123 can then evaluate the response and performance of the digital twin model 130 in the set virtual emergencies. The emergency condition imposition module 123 can also predict adjustments necessary to ensure the safety and stability of the ammonia cracking plant.

[0062] Under the imposed emergency conditions, a step of collecting data from the digital twin model is performed (S400).

[0063] A step of comparing first data when an emergency condition is imposed with second data when no emergency condition is imposed is performed (S500).

[0064] Regarding steps S400 and S500, for example, referring to FIG. 1, the data collection and comparison module 124 collects data from the digital twin model 130 under imposed emergency conditions, compares first data when the emergency condition is imposed with second data when the emergency condition is not imposed, and generates comparison data including the results of comparing the first data and the second data, thereby identifying weaknesses in the system 100 that may occur under each emergency situation and the degree of vulnerability for each replication model.

[0065] A step of generating a control scenario for a preset emergency scenario based on the comparison data is performed (S600).

[0066] Regarding step S600, for example, referring to FIG. 1 , the scenario generation module 125 can generate a control scenario for a preset emergency scenario based on the comparison data, and generate control scenarios for a variety of multiple potential emergency situations using the comparison data between the first data and the second data.

[0067] Meanwhile, the disclosed embodiments may be embodied in the form of a storage medium storing computer-executable instructions. The instructions may be stored in the form of program code, and when executed by a processor, may generate program modules to perform the operations of the disclosed embodiments. The storage medium may be embodied as a computer-readable storage medium.

[0068] A computer-readable storage medium includes any type of storage medium that stores instructions that can be decoded by a computer. For example, it may be a read-only memory (ROM), a random access memory (RAM), a magnetic tape, a magnetic disk, a flash memory, an optical data storage device, etc. The disclosed embodiments have been described above with reference to the accompanying drawings. A person skilled in the art to which this disclosure pertains would understand that the present disclosure can be implemented in forms different from the disclosed embodiments without changing the technical spirit or essential features of the present disclosure. It should be understood that the disclosed embodiments are illustrative and not limiting.

Claims

1. 1. A system for managing an ammonia cracking plant, comprising: a model generation module for generating a digital twin model including a replica model of the physical components of the ammonia cracking plant; an input module for inputting an estimated actual dynamic energy demand and output information of an ammonia cracker included in the ammonia cracking plant into the digital twin model; an emergency condition imposition module that sets a plurality of virtual emergencies in the digital twin model to prepare for potential emergencies, so as to impose emergency conditions on the replica model of the physical component for a preset emergency scenario; a data collection and comparison module that collects data from the digital twin model under the imposed emergency conditions in accordance with a plurality of set virtual emergency situations, and compares various first data when the emergency conditions are imposed with second data when the emergency conditions are not imposed; a scenario generation module that generates a control scenario for the preset emergency scenario based on a comparison result between the first data and the second data.

2. The physical components of the ammonia decomposition plant include: The ammonia decomposition device, a sensor, and a control device are included, The model generation module:

10. The system of claim 1, further comprising: updating the digital twin model with real-time data from the ammonia cracking plant.

3. The input module includes: The system of claim 1 , wherein the digital twin model compares a difference between the actual required dynamic energy demand and the output amount of the output information of the ammonia cracking plant.

4. The emergency condition imposition module:

10. The system of claim 1, wherein the system predicts adjustments necessary to ensure the safety and stability of the ammonia cracking plant.

5. The data collection and comparison module: The system of claim 1 , wherein the system identifies weaknesses in the system that may occur in each emergency and the degree of vulnerability for each replication model based on the collected data.

6. The scenario generation module The system of claim 1 , further comprising: generating control scenarios for potential emergency situations using comparison data between the first data and the second data.

7. The digital twin model is a plant control unit corresponding to a replica model of the control device that controls the ammonia decomposition device; and a data collector that collects the real-time data.

8. The physical components of the ammonia decomposition plant include: further comprising a feed blower, a flow control valve, and at least one reaction unit; The system of claim 2 , wherein the sensors include a temperature sensor and a pressure sensor.

9. The at least one reaction unit comprises:

10. The system of claim 8, comprising a plurality of reaction sections receiving a flow rate of feed for a reforming reaction and a flow rate of feed for a combustion reaction, and a combustion section outputting combustion flue gas.

10. 1. A method for operating an ammonia cracking plant, comprising: generating a digital twin model that includes replica models of physical components of the ammonia cracking plant; A step of inputting an estimated actual dynamic energy demand and output information of an ammonia cracker included in the ammonia cracking plant into the digital twin model; Setting a plurality of virtual emergencies in the digital twin model to prepare for potential emergencies, for imposing emergency conditions on the replica model of the physical component for a preset emergency scenario; Collecting data from the digital twin model under the imposed emergency conditions in accordance with a plurality of set virtual emergency situations; comparing various first data when the emergency condition is imposed with second data when the emergency condition is not imposed; generating a control scenario for the preset emergency scenario based on a comparison result between the first data and the second data.

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