Patent Application
20250025851
This application claims priority under 35 U.S.C. § 119 to Korean Patent Application No. 10-2023-0095480, filed on Jul. 21, 2023 in the Korean Intellectual Property Office, the disclosure of which is incorporated herein by reference in its entirety.
The present invention disclosure relates to a system and a method for managing an ammonia cracking plant.
Recently, as various environmental problems are becoming a major issue throughout the world, demand for the introduction of eco-friendly alternative energy instead of existing internal combustion engines not only for general vehicles but also for heavy equipment such as an excavator is increasing. Thereby, a fuel cell system which uses fuel cells (FCs) as a power source has been in the spotlight.
In order to ensure a smooth operation and a high performance of the fuel cell system, the role of an Energy Management System (EMS) is important to appropriately determine how to distribute power demands between the power sources. To this end, stable and reliable operation of the EMS is required.
In a situation where a plurality of pipes exist, 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 the corresponding pipe. It is difficult to describe the complex interaction between different components of the system by conventional methods. To solve this problem, digital twins (DTs) are being developed for providing an accurate real-time simulation of entire physical systems.
It is an object of the present invention disclosure to provide a system and a method capable of ensuring stable operation of an ammonia cracking plant under emergency situation conditions.
To achieve the above object, according to an aspect of the present invention, there is provided a system for managing an ammonia cracking plant, the system including: a model generation module configured to generate a digital twin model including a replication model of a physical component of the ammonia cracking plant; an input module configured to input dynamic energy requirement and output information of an ammonia cracking apparatus included in the ammonia cracking plant into the digital twin model; an emergency condition imposition module configured to impose, for a preset emergency scenario, an emergency condition on the replication model of the physical component; a data collection and comparison module configured to collect data from the digital twin model under the imposed emergency condition, and compare first data when the emergency condition is imposed and second data when the emergency condition is not imposed; and a scenario generation module configured to generate a control scenario for the preset emergency scenario based on comparison results of the first data and the second data.
According to an embodiment, the physical component of the ammonia cracking plant may include: the ammonia cracking apparatus, a sensor, and a control device, and the model generation module updates the digital twin model using real-time data of the ammonia cracking plant.
According to an embodiment, the input module may compare a difference between a dynamic energy requirement actually needed for the digital twin model and an output quantity of the output information of the ammonia cracking plant.
According to an embodiment, the emergency condition imposition module may be configured to: set a plurality of virtual emergency situations in the digital twin model to prepare for potential emergency situations; evaluate response and performance of the digital twin model in the set virtual emergency situation; and predict adjustments required to ensure safety and stability of the ammonia cracking plant.
According to an embodiment, the data collection and comparison module may identify weaknesses of the system which may occur in each emergency situation and a degree of vulnerability for each replication model based on the data.
According to an embodiment, the scenario generation module may generate a control scenario for the potential emergency situation using comparative data between the first data and the second data.
According to an embodiment, the digital twin model may include: a plant control unit corresponding to a replication model for the control device configured to control the ammonia cracking apparatus; and a data collection unit configured to collect the real-time data.
According to an embodiment, the physical component of the ammonia cracking plant may further include a feed blower, a flow rate control valve, and at least one reaction unit, wherein the sensor may include a temperature sensor and a pressure sensor.
According to an embodiment, the at least one reaction unit may include: a plurality of reaction parts configured to 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 unit configured to output a combustion flue gas.
According to another aspect of the present invention, there is provided a method for managing an ammonia cracking plant, the method including: generating a digital twin model comprising a replication model of a physical component of the ammonia cracking plant; inputting a dynamic energy requirement and output information of an ammonia cracking apparatus included in the ammonia cracking plant into the digital twin model; imposing, for a preset emergency scenario, an emergency condition on the replication model of the physical component; collecting data from the digital twin model under the imposed emergency condition; comparing first data when the emergency condition is imposed and second data when the emergency condition is not imposed; and generating a control scenario for the preset emergency scenario based on comparison results of the first data and the second data.
According to an embodiment of the present invention disclosure, by ensuring stable operation of the ammonia cracking plant under emergency situation conditions, the reliability of the system may be improved.
In addition, according to an embodiment of the present invention disclosure, by designing the digital twin model to closely imitate operations of the plant under various conditions, there are effects of monitoring the plant in real time, analyzing and optimizing the operation thereof.
In addition, according to an embodiment of the present invention disclosure, by establishing a scenario of appropriate actions to be implemented in response to a specific emergency situation in advance, the safety of the system may be ensured.
Further, according to an embodiment of the present invention disclosure, there are effects of providing assistance in identifying potential regions for improvement, and ultimately contributing to the overall sustainability and cost-effectiveness of the plant.
The above and other objects, features and other advantages of the present invention will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings, in which:
Hereinafter, the present invention disclosure will be described in more detail through example embodiments with reference to the accompanying drawings. However, the embodiments are merely illustrative and the present invention disclosure is not limited to the specific embodiments described by way of example.
The same reference numerals are denoted to the same components throughout the present invention disclosure. The present invention disclosure does not describe all elements of the embodiments, and general contents in the technical field to which the present invention disclosure pertains or overlapping contents between the embodiments will not be described. The terms ‘unit, module, member and block’ used herein may be implemented as software or hardware, and depending on the embodiments, a plurality of ‘units, modules, members and blocks’ may be implemented as one component, or one ‘part, module, member, or block’ may include a plurality of components.
Throughout the specification, when the explanatory phrase a part is “connected” to another part is used, this includes not only the case where the part is “directly connected” to the other part, but also the case where the part is “indirectly connected” to the other part, and the indirect connection includes connection through a wireless communication network.
In addition, when the explanatory phrase a part “comprises or includes” a component is used, this means that the part may further include the component without excluding other components, unless there is a description opposite thereto.
Throughout the specification, when the explanatory phrase a member is located “on” another member is used, this includes not only the case where the member is in contact with the other member, but also the case where another member exists between the two members.
The singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The identification numerals for each operation are used for the convenience of description. The identification numerals do not describe the order of each operation, and each operation may be performed differently from the specified order unless a specific order is clearly described in the context.
In this specification, the ‘device according to the present invention disclosure’ includes all various devices that can perform computational processing and provide results thereof to a user. For example, the device according to the present invention disclosure may include all of a computer, a server device and a portable terminal, or may be any form thereof.
Here, the computer may include, for example, a laptop or desktop computer, laptop PC, tablet PC, slate PC, and the like equipped with a web browser.
The server device is a server that processes information by performing communication with an external device, and may include an application server, computing server, database server, file server, game server, mail server, proxy server and web server.
The portable terminal is, for example, a wireless communication device with which portability and mobility are assured, and may include: all types of handheld wireless communication devices such as a personal communication system (PCS), global system for mobile communications (GSM), personal digital cellular (PDC), personal handy phone system (PHS), personal digital assistant (PDA), international mobile telecommunication (IMT)-2000, code division multiple access (CDMA)-2000, wideband code division multiple access (W-CDMA), wireless broadband internet (WiBro) terminal, smart phone, and the like; and wearable devices such as a watch, ring, bracelet, anklet, necklace, glasses, contact lenses, head-mounted-device (HMD), and the like.
Referring to
The physical plant 110 may be an ammonia cracking plant. However, it is not limited thereto. The physical plant 110 implemented as the ammonia cracking plant may include an ammonia cracking apparatus 111, a control device 112 configured to control the ammonia cracking apparatus 111, a feed blower 113, a flow rate control valve 114, a reaction unit 115, a temperature sensor 116, and a pressure sensor 117. The temperature sensor 116 and/or the pressure sensor 117 may be referred to also simply as a sensor. In other words, the term sensor as used herein may be a temperature sensor, or a pressure sensor or both a temperature sensor and a pressure sensor. One or more sensors may be employed as may be needed.
The model generation module 121 may generate the digital twin model 130. The digital twin model 130 may include a replication model of a physical component of the physical plant 110. The physical component of physical plant 110 may be, for example, physical components of the ammonia cracking plant. In this case, the physical component of the physical plant 110 may include the ammonia cracking apparatus 111, the control device 112, the feed blower 113, the flow rate control valve 114, the reaction unit 115, the temperature sensor 116, and the pressure sensor 117. The replication model included in the digital twin model 130 may include an ammonia cracking apparatus 131, a control device 132, a feed blower 133, a flow rate control valve 134, a reaction unit 135, a temperature sensor 136, and a pressure sensor 137.
The model generation module 121 may continuously update the digital twin model 130 using real-time data of the ammonia cracking plant for more accurate and specific simulation and prediction.
The input module 122 may input a dynamic energy requirement and output information of the physical plant 110 to the digital twin model 130. For example, the input module 122 may input the dynamic energy requirement to the digital twin model 130, and input the output information of the ammonia cracking apparatus 111 included in the ammonia cracking plant.
The input module 122 may compare a difference between the dynamic energy requirement actually required for the digital twin model 130 and an output quantity of the output information of the ammonia cracking plant.
The emergency condition imposition module 123 may impose, for a preset emergency scenario, emergency conditions on the replication model of the physical components of the physical plant 110.
The emergency condition imposition module 123 may set a plurality of various virtual emergency situations in the digital twin model 130 to prepare for potential emergency situations. In addition, the emergency condition imposition module 123 may evaluate response and performance of the digital twin model 130 in the set virtual emergency situation. Further, the emergency condition imposition module 123 may predict adjustments required to ensure the safety and stability of the ammonia cracking plant.
The data collection and comparison module 124 may collect data from the digital twin model 130 under the imposed emergency conditions. In addition, the data collection and comparison module 124 may compare first data when the emergency condition is imposed and second data when the emergency condition is not imposed. Then, comparative data including results of comparing the first data and the second data may be generated.
Based on the data, the data collection and comparison module 124 may identify weaknesses of the system 100 which may occur in each emergency situation and a degree of vulnerability for each replication model.
The scenario generation module 125 may generate a control scenario for the preset emergency scenario based on the comparative data.
The scenario generation module 125 may generate control scenarios for a plurality of potential emergency situations using the comparative data between the first data and the second data.
According to the above description, by ensuring stable operation of the ammonia cracking plant under emergency situation conditions, the reliability of the system 100 may be improved.
In addition, according to the above description, by designing the digital twin model to closely imitate operations of the plant under various conditions, the system 100 allows monitoring the plant in real time, and analyzing and optimizing the plant operation.
In addition, according to the above description, by establishing a scenario of appropriate actions to be implemented in response to a specific emergency situation in advance, the safety of the system may be ensured.
Further, according to the above description, other technical effects obtained by the system include providing assistance (e.g., data) in identifying potential regions for improvement, and ultimately contributing to the overall sustainability and cost-effectiveness of the plant.
Referring to
The dynamic load input 210 may correspond to the above-described dynamic energy requirement. The dynamic load input 210 may be an input to the digital twin model 220.
The digital twin model 220 may include a plant control unit 221 corresponding to the replication model for the control device configured to control the ammonia cracking apparatus, and a data collection unit 222 configured to collect real-time data. The data collection unit 222 may receive the dynamic load input 210 and the first to tenth information 11, 12, 13, 14, 15, 16, 17, 18, 19 and
I10. The data collection unit 222 may receive the flow rate of a feed for a reforming reaction and the flow rate of a feed for a combustion reaction provided through the first to fourth control valves 251, 252, 253 and 254 as inputs.
The number of first to Nth reaction units 2301 to 230_N may be N as shown in
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 and 253. The combustion reaction feed may be input to the second blower 242. The combustion reaction feed may include fuel and air as a feed. The second blower 242 may provide the combustion reaction feed to the second and fourth control valves 252 and 254.
First, an operation of generating a digital twin model including a replication model of a physical component of the ammonia cracking plant is performed (S100).
In an embodiment, in relation to the operation S100 with reference to
Then, an operation of inputting a dynamic energy requirement and output information of the ammonia cracking apparatus included in the ammonia cracking plant into the digital twin model is performed (S200).
In an embodiment, in relation to the operation S200 with reference to
Thereafter, an operation of imposing, for a preset emergency scenario, an emergency condition on the replication model of the physical components is performed (S300).
In an embodiment, in relation to the operation $300 with reference to
Next, an operation of collecting data from the digital twin model under the imposed emergency condition is performed (S400).
Then, an operation of comparing first data when the emergency condition is imposed and second data when the emergency condition is not imposed is performed (S500).
In an embodiment, in relation to the operation S400 and operation S500 with reference to
Finally, an operation of generating a control scenario for the preset emergency scenario based on the comparative data is performed (S600).
In an embodiment, in relation to the operation $600 with reference to
Meanwhile, the disclosed embodiments may be implemented in the form of a recording medium which stores instructions executable by a computer. The instructions may be stored in the form of program code, and when executed by the processor, may generate a program module to perform operations of the disclosed embodiments. The recording medium may be implemented as a computer-readable recording medium.
The computer-readable recording medium may include all types of recording media in which instructions that can be decoded by the computer are stored. For example, there may be a read only memory (ROM), random access memory (RAM), magnetic tape, magnetic disk, flash memory, optical data storage device and the like.
As above, the disclosed embodiments have been described with reference to the accompanying drawings. It will be understood by persons skilled in the art to which the present invention disclosure pertains that the present invention disclosure may be embodied in forms different from the disclosed embodiments without changing the technical idea or essential features of the present invention disclosure. The disclosed embodiments are illustrative, and should not be interpreted as limiting.
| Number | Date | Country | Kind |
|---|---|---|---|
| 10-2023-0095480 | Jul 2023 | KR | national |
