System and method for recommending energy simulation component for digital twin-based virtual verification complex

Abstract

A system for recommending an energy simulation component, according to one embodiment of the present invention, comprises: a type recommendation unit for storing simulation type information and transmitting same to a researcher terminal, and receiving, from the researcher terminal, selected simulation type information according to a selection of the simulation type information; a resource recommendation unit for storing distributed resource information and grid model information and transmitting same to the researcher terminal, and receiving, from the researcher terminal, selective distributed resource information according to a selection of the distributed resource information and selected grid model information according to a selection of the grid model information; a data function recommendation unit for storing data set information and function module information and transmitting same to the researcher terminal, and receiving, from the researcher terminal, selection data set information according to a selection of the data set information and selected function module information according to a selection of the function module information; a virtual environment unit for generating a virtual environment; and a usage analysis unit for receiving, from the researcher terminal, a usage log by the researcher terminal and storing same, generating analysis information according to the usage log, and generating recommendation information according to the simulation type information on the basis of the analysis information.

Description

Recommendation system and method for energy simulation components for a digital twin-based virtual demonstration complex

[0001] The present invention relates to a system and method for recommending energy simulation components, and more particularly, to a system and method for recommending energy simulation components for a digital twin-based virtual demonstration complex, which provides researchers with components necessary for conducting simulations for energy-related technology research and allows them to select them, thereby enabling research to be conducted in a virtual environment according to the researcher's selection.

[0002] A digital twin is a virtual model that replicates a physical object or system in the real world. Through these digital twins, the status of real-world objects or systems can be monitored in real time, and future situations can be predicted and simulated.

[0003] Furthermore, virtual verification refers to verifying the performance of objects or systems in a virtual environment using digital twin technology. For example, in the automotive industry, digital twins are used to pre-test the performance and safety of new vehicles in a virtual environment, allowing for improvements before actual production if any issues are identified. In the energy industry, digital twins are used to predict distributed resource power generation in a virtual environment based on distributed resources and related data, and then the design of distributed resources can be modified based on the predicted power generation.

[0004] By utilizing digital twins and virtual demonstrations, the time and cost associated with building and testing real-world objects or systems can be significantly reduced, and real-world objects or systems can be built more safely and efficiently. However, using digital twins and virtual demonstrations, there are challenges in selecting appropriate components for building virtual environments and conducting simulations, as well as selecting and applying appropriate data for these components.

[0005] The technical task to be achieved by the energy simulation component recommendation system and method according to the technical idea of ​​the present invention is to provide an energy simulation component recommendation system and method that enables components and data for energy technology research and development to be easily selected and appropriately utilized.

[0006] In addition, the technical task to be achieved by the energy simulation component recommendation system and method according to the technical idea of ​​the present invention is to provide an energy simulation component recommendation system and method that appropriately provides a virtual environment for research and development and enables research results to be generated through the provided virtual environment.

[0007] In addition, the technical task to be achieved by the energy simulation component recommendation system and method according to the technical idea of ​​the present invention is to provide an energy simulation component recommendation system and method that shortens the time required for research and development and enables research and development to be conducted intensively.

[0008] The technical tasks to be achieved by the energy simulation component recommendation system and method according to the technical idea of ​​the present invention are not limited to the tasks mentioned above, and other tasks not mentioned will be clearly understood by those skilled in the art from the description below.

[0009] An energy simulation component recommendation system according to one embodiment of the technical idea of ​​the present invention is an energy simulation component recommendation system connected to a researcher terminal through a network, comprising: a type recommendation unit that stores simulation type information, transmits the simulation type information to the researcher terminal, and receives selected simulation type information from the researcher terminal according to a selection of the simulation type information transmitted to the researcher terminal; a resource recommendation unit that stores distributed resource information and grid model information, transmits the distributed resource information and the grid model information to the researcher terminal, and receives selected distributed resource information according to a selection of the distributed resource information transmitted to the researcher terminal and selected grid model information according to a selection of the grid model information transmitted to the researcher terminal from the researcher terminal; a data function recommendation unit that stores data set information and function module information, transmits the data set information and the function module information to the researcher terminal, and receives selected data set information according to a selection of the data set information transmitted to the researcher terminal and selected function module information according to a selection of the function module information transmitted to the researcher terminal from the researcher terminal; It may be characterized by including a virtual environment section that creates a virtual environment based on selected simulation type information, selected distributed resource information, selected grid model information, selected data set information, and selected function module information; and a usage analysis section that receives and stores usage logs transmitted by a researcher terminal from the researcher terminal, creates analysis information based on the usage logs, and creates recommendation information based on simulation type information based on the analysis information.

[0010] In addition, simulation type information includes simulation type and type content, distributed resource information includes distributed resource type, distributed resource location, and distributed resource capacity, grid model information includes grid model type, grid model specification, and grid model content, data set information includes data type and data collection period, and function module information may include module name and function module content.

[0011] In addition, the type recommendation unit generates a simulation query corresponding to the simulation type information, and the type recommendation unit transmits the simulation query to a researcher terminal, receives a simulation answer in natural language form for the simulation query from the researcher terminal, performs natural language processing on the simulation answer, analyzes the simulation query and the simulation answer to extract at least one piece of simulation type information, and transmits the extracted simulation type information to the researcher terminal that transmitted the simulation answer.

[0012] In addition, the resource recommendation unit extracts distributed resource information corresponding to the selected simulation type information, and generates a distributed resource query corresponding to the extracted distributed resource information, wherein the resource recommendation unit transmits the distributed resource query to a researcher terminal, receives a distributed resource answer in natural language form for the distributed resource query from the researcher terminal, performs natural language processing on the distributed resource answer, analyzes the distributed resource query and the distributed resource answer to extract at least one piece of distributed resource information, and transmits the extracted distributed resource information to the researcher terminal that transmitted the distributed resource answer.

[0013] In addition, the resource recommendation unit extracts grid model information corresponding to the selected distributed resource information, and generates a grid model query corresponding to the extracted grid model information, wherein the resource recommendation unit transmits the grid model query to a researcher terminal, receives a grid model answer in a natural language format for the grid model query from the researcher terminal, performs natural language processing on the grid model answer, analyzes the grid model query and the grid model answer to extract at least one piece of grid model information, and transmits the extracted grid model information to the researcher terminal that transmitted the grid model answer.

[0014] In addition, the data function recommendation unit extracts data set information corresponding to the selected distributed resource information and the selected grid model information, and generates a data set query corresponding to the extracted data set information, wherein the data function recommendation unit transmits the data set query to a researcher terminal, receives a data set answer in a natural language format for the data set query from the researcher terminal, performs natural language processing on the data set answer, analyzes the data set query and the data set answer to extract at least one data set information, and transmits the extracted data set information to the researcher terminal that transmitted the data set answer.

[0015] In addition, the data function recommendation unit extracts function module information corresponding to the selected data set information, and generates a function module query corresponding to the extracted function module information, wherein the data function recommendation unit transmits the function module query to a researcher terminal, receives a function module response in natural language form for the function module query from the researcher terminal, performs natural language processing on the function module response, analyzes the function module query and the function module response to extract at least one function module information, and transmits the extracted function module information to the researcher terminal that transmitted the function module response.

[0016] In addition, the virtual environment unit can generate a virtual environment by calculating the data capacity that can process a data set according to the selected data set information in the simulation type according to the selected simulation type information, calculating the specifications of the hardware that can execute the function module according to the selected function module information, and setting up a cloud-based data storage based on the data capacity and a cloud-based server based on the specifications of the hardware.

[0017] In addition, when a researcher terminal is connected to a virtual environment and a simulation is performed in the virtual environment, the researcher terminal generates a usage log and transmits it to the usage analysis unit for storage, and the usage analysis unit can generate analysis information by analyzing the interaction of distributed resources according to the selected distributed resource information, grid models according to the selected grid model information, data sets according to the selected data set information, and functional modules according to the selected functional module information based on the usage log.

[0018] In addition, a method for recommending energy simulation components according to an embodiment of the technical idea of ​​the present invention comprises the steps of: (a) transmitting simulation type information stored in a type recommendation unit to a researcher terminal, and receiving selected simulation type information from the researcher terminal according to a selection of the simulation type information transmitted to the researcher terminal; (b) transmitting distributed resource information stored in a resource recommendation unit to a researcher terminal, and receiving selected distributed resource information from the researcher terminal according to a selection of the distributed resource information transmitted to the researcher terminal; (c) transmitting grid model information stored in a resource recommendation unit to a researcher terminal, and receiving selected grid model information from the researcher terminal according to a selection of the grid model information transmitted to the researcher terminal; (d) transmitting data set information stored in a data function recommendation unit to a researcher terminal, and receiving selected data set information from the researcher terminal according to a selection of the data set information transmitted to the researcher terminal; (e) transmitting function module information stored in a data function recommendation unit to a researcher terminal, and receiving selected function module information from the researcher terminal according to a selection of the function module information transmitted to the researcher terminal; (f) a step of the virtual environment unit generating a virtual environment based on selected simulation type information, selected distributed resource information, selected grid model information, selected data set information, and selected function module information; and (g) a step of the usage analysis unit receiving and storing usage logs transmitted from the researcher terminal, generating analysis information based on the usage logs, and generating recommendation information based on simulation type information based on the analysis information.

[0019] In addition, in step (a), the type recommendation unit generates a simulation query corresponding to the simulation type information, the type recommendation unit transmits the simulation query to a researcher terminal, receives a simulation answer in natural language form for the simulation query from the researcher terminal, performs natural language processing on the simulation answer, analyzes the simulation query and the simulation answer to extract at least one piece of simulation type information, and transmits the extracted simulation type information to the researcher terminal that transmitted the simulation answer.

[0020] In addition, in step (b), the resource recommendation unit extracts distributed resource information corresponding to the selected simulation type information, and generates a distributed resource query corresponding to the extracted distributed resource information, wherein the resource recommendation unit transmits the distributed resource query to a researcher terminal, receives a distributed resource answer in natural language form for the distributed resource query from the researcher terminal, performs natural language processing on the distributed resource answer, analyzes the distributed resource query and the distributed resource answer to extract at least one piece of distributed resource information, and transmits the extracted distributed resource information to the researcher terminal that transmitted the distributed resource answer.

[0021] In addition, in step (c), the resource recommendation unit extracts grid model information corresponding to the selected distributed resource information, and generates a grid model query corresponding to the extracted grid model information, wherein the resource recommendation unit transmits the grid model query to a researcher terminal, receives a grid model answer in natural language form for the grid model query from the researcher terminal, performs natural language processing on the grid model answer, analyzes the grid model query and the grid model answer to extract at least one piece of grid model information, and transmits the extracted grid model information to the researcher terminal that transmitted the grid model answer.

[0022] In addition, in step (d), the data function recommendation unit extracts data set information corresponding to the selected distributed resource information and the selected grid model information, and generates a data set query corresponding to the extracted data set information, wherein the data function recommendation unit transmits the data set query to a researcher terminal, receives a data set answer in natural language form for the data set query from the researcher terminal, performs natural language processing on the data set answer, analyzes the data set query and the data set answer to extract at least one piece of data set information, and transmits the extracted data set information to the researcher terminal that transmitted the data set answer.

[0023] In addition, in step (e), the data function recommendation unit extracts function module information corresponding to the selected data set information, generates a function module query corresponding to the extracted function module information, and the data function recommendation unit transmits the function module query to a researcher terminal, receives a function module response in natural language form for the function module query from the researcher terminal, performs natural language processing on the function module response, analyzes the function module query and the function module response to extract at least one function module information, and transmits the extracted function module information to the researcher terminal that transmitted the function module response.

[0024] In addition, in step (f), the virtual environment unit can generate a virtual environment by calculating the data capacity that can process a data set according to the selected data set information in the simulation type according to the selected simulation type information, calculating the specifications of hardware that can execute a function module according to the selected function module information, and setting up a cloud-based data storage based on the data capacity and a cloud-based server based on the specifications of the hardware.

[0025] In addition, in step (g), when the researcher terminal is connected to the virtual environment and a simulation is performed in the virtual environment, the researcher terminal generates a usage log and transmits it to the usage analysis unit for storage, and the usage analysis unit can generate analysis information by analyzing the interaction of distributed resources according to the selected distributed resource information, grid models according to the selected grid model information, data sets according to the selected data set information, and functional modules according to the selected functional module information based on the usage log.

[0026] The energy simulation component recommendation system and method according to embodiments of the technical idea of ​​the present invention have the following effects.

[0027] (1) Enable researchers to easily select and appropriately utilize components and data for energy technology research and development.

[0028] (2) Researchers are provided with a virtual environment for research and development and can generate research results through the provided virtual environment.

[0029] (3) It allows researchers to focus on research and development through shortened research and development time.

[0030] However, the effects that can be achieved by the energy simulation component recommendation system and method according to one embodiment of the present invention are not limited to those mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0031] To facilitate a more thorough understanding of the drawings cited herein, a brief description of each drawing is provided.

[0032] FIG. 1 is a diagram illustrating an energy simulation component recommendation system according to one embodiment of the present invention.

[0033] FIG. 2 is a flowchart illustrating a method for recommending energy simulation components according to one embodiment of the present invention.

[0034] The present invention is susceptible to various modifications and embodiments. Specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that the present invention encompasses all modifications, equivalents, and alternatives falling within the spirit and technical scope of the present invention.

[0035] In describing the present invention, detailed descriptions of related known technologies will be omitted if they are deemed to unnecessarily obscure the gist of the present invention. Furthermore, numbers (e.g., "first," "second," etc.) used throughout the description of this specification are merely identifiers used to distinguish one component from another.

[0036] Additionally, in this specification, when a component is referred to as being “connected” or “connected” to another component, it should be understood that the component may be directly connected or connected to the other component, but may also be connected or connected via another component in between, unless there is a specific description to the contrary.

[0037] In addition, the components expressed as "~part" in this specification may be two or more components combined into one component, or one component may be divided into two or more components with more detailed functions. In addition, each component described below may additionally perform some or all of the functions performed by other components in addition to its own main function, and of course, some of the main functions performed by each component may be exclusively performed by other components.

[0038] Hereinafter, embodiments according to the technical idea of ​​the present invention will be described in detail one by one.

[0039] FIG. 1 is a diagram illustrating an energy simulation component recommendation system (100) according to one embodiment of the present invention.

[0040] As illustrated in FIG. 1, an energy simulation component recommendation system (100) according to one embodiment of the present invention can be connected to a researcher terminal (10) through a network (1), and can include a type recommendation unit (101), a resource recommendation unit (102), a data function recommendation unit (103), a virtual environment unit (104), and a usage analysis unit (105). Here, a researcher means a person who conducts energy-related research and development by conducting energy-related simulations, and can conduct research and development through digital twins and virtual verification by connecting to the energy simulation component recommendation system (100) using the researcher terminal (10) and exchanging signals with the energy simulation component recommendation system (100).

[0041] Additionally, the type recommendation unit (101), resource recommendation unit (102), data function recommendation unit (103), virtual environment unit (104), and usage analysis unit (105) may include at least one of a processor, a memory, and a data transceiver.

[0042] The energy simulation component recommendation system (100) may be operated by displaying a web page through a web browser operated on a researcher terminal (10) and allowing access to the energy simulation component recommendation system (100) after logging in on the web page, or by installing an application capable of accessing the energy simulation component recommendation system (100) on the researcher terminal (10).

[0043] The researcher terminal (10) may be implemented as a computer capable of connecting to a remote server or terminal via a network (1). Here, the computer may include, for example, a notebook, desktop, or laptop equipped with a web browser. In addition, the researcher terminal (10) may be implemented as a terminal device capable of connecting to a remote server or terminal via the network (1). The terminal device may include all types of handheld-based wireless communication devices such as, for example, a wireless communication device that guarantees portability and mobility, such as a 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) terminal, smartphone, smartpad, tablet PC, etc.

[0044] Here, the network (1) refers to a connection structure that enables information exchange between each node, such as multiple terminals and servers, and examples of such networks include, but are not limited to, a 3GPP (3rd Generation Partnership Project) network, an LTE (Long Term Evolution) network, a 5G network, a WIMAX (World Interoperability for Microwave Access) network, the Internet, a LAN (Local Area Network), a Wireless LAN (Wireless Local Area Network), a WAN (Wide Area Network), a PAN (Personal Area Network), a Bluetooth network, a satellite broadcasting network, an analog broadcasting network, and a DMB (Digital Multimedia Broadcasting) network.

[0045] The type recommendation unit (101) can store simulation type information. Here, the simulation type information means information on a simulation system, which is a virtual demonstration complex system for energy-related research and development, and may include simulation type, type content, etc. In addition, the simulation type means a name according to the type of simulation system, and may include a distributed resource-based power system, a microgrid system, an integrated power plant system, a virtual power plant (VPP) system, an energy trading system, a vehicle-to-grid (V2G) system, etc., and the type content may include content on a simulation system according to the simulation type. In the present embodiment, the simulation type information may be composed of multiple pieces according to the simulation type.

[0046] Additionally, the type recommendation unit (101) can transmit simulation type information to the researcher terminal (10). Here, the type recommendation unit (101) can transmit all of the stored simulation type information to the researcher terminal (10).

[0047] Meanwhile, when a researcher wants to conduct a simulation through a virtual environment by an energy simulation component recommendation system (100), the researcher can transmit a desired signal to the type recommendation unit (101) through the researcher terminal (10). When the type recommendation unit (101) receives the desired signal, the type recommendation unit (101) can transmit simulation type information to the researcher terminal (10) that transmitted the desired signal.

[0048] In addition, the researcher terminal (10) can receive and output simulation type information. Here, the researcher can select at least one piece of simulation type information through the researcher terminal (10), and the researcher terminal (10) can generate the selected at least one piece of simulation type information as selected simulation type information and transmit the selected simulation type information to the type recommendation unit (101).

[0049] Meanwhile, the type recommendation unit (101) can generate a simulation query based on simulation type information. Here, the simulation query may refer to a question necessary for selecting and determining simulation type information, and may include, for example, "What is your research topic?", "Where is your research-related institution?", "Where is your research target region?", etc. In addition, the type recommendation unit (101) can transmit the simulation query to the researcher terminal (10) that transmitted the aforementioned request signal.

[0050] The type recommendation unit (101) can transmit a simulation query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the simulation query, and the researcher can input a simulation answer to the simulation query through the researcher terminal (10), and the researcher terminal (10) can transmit the simulation answer to the type recommendation unit (101). In addition, the type recommendation unit (101) can analyze the simulation query and the simulation answer to extract at least one piece of simulation type information, and transmit the extracted simulation type information to the researcher terminal (10). Here, the simulation answer is in natural language, and the type recommendation unit (101) can perform natural language processing of the simulation answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the simulation answer. In addition, the researcher can check the extracted simulation type information through the researcher terminal (10), and at least one piece of extracted simulation type information can be selected in the researcher terminal (10) and generated as selected simulation type information.

[0051] In addition, after receiving a simulation answer, the type recommendation unit (101) can transmit a new simulation query corresponding to the simulation answer to the researcher terminal (10) that transmitted the simulation answer. Here, the new simulation query can be generated by considering the simulation query and the simulation answer.

[0052] Additionally, the type recommendation unit (101) can repeatedly transmit corresponding simulation queries and receive simulation responses to the simulation queries. Accordingly, the type recommendation unit (101) can analyze multiple simulation queries and simulation responses to the multiple simulation queries to extract simulation type information. The extracted simulation type information can be used to generate selected simulation type information.

[0053] The resource recommendation unit (102) can store distributed resource information. Here, the distributed resource information refers to information on distributed resources applied in the simulation system, and may include distributed resource types, distributed resource locations, and distributed resource capacities. In addition, the distributed resource types may include fuel cells, liquefied natural gas gasification, hydrogen energy generation, geothermal power generation, biopower generation, wave power generation, hydropower generation, wind power generation, waste-to-energy generation, solar power generation, and solar power generation, and the distributed resource locations may include latitude and longitude for the installation locations of the distributed resources, and the distributed resource capacity may be a numerical value indicating the scale of the distributed resources. In the present embodiment, the distributed resource information may include distributed resource locations and distributed resource capacities for each distributed resource type.

[0054] In addition, the resource recommendation unit (102) can transmit distributed resource information to the researcher terminal (10). Here, the resource recommendation unit (102) can transmit all of the plurality of distributed resource information stored to the researcher terminal (10). In addition, the researcher terminal (10) can receive and output the distributed resource information. Here, the researcher can select at least one piece of distributed resource information through the researcher terminal (10), and the researcher terminal (10) can generate the at least one piece of selected distributed resource information as selected distributed resource information and transmit the selected distributed resource information to the resource recommendation unit (102).

[0055] Meanwhile, the resource recommendation unit (102) can extract distributed resource information corresponding to the selection simulation type information and generate a distributed resource query based on the extracted distributed resource information. Here, the distributed resource query may refer to a question necessary for selecting and deciding on distributed resource information, and may include, for example, "What distributed resource do you want to use?", "Where do you want to install the distributed resource?", and "What is the scale of your distributed resource?"

[0056] The resource recommendation unit (102) can transmit a distributed resource query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the distributed resource query, and the researcher can input a distributed resource answer to the distributed resource query through the researcher terminal (10), and the researcher terminal (10) can transmit the distributed resource answer to the resource recommendation unit (102). In addition, the resource recommendation unit (102) can analyze the distributed resource query and the distributed resource answer to extract at least one piece of distributed resource information, and transmit the extracted distributed resource information to the researcher terminal (10). Here, the distributed resource answer is in natural language, and the resource recommendation unit (102) can perform natural language processing of the distributed resource answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the distributed resource answer. In addition, the researcher can check the extracted distributed resource information through the researcher terminal (10), and at least one extracted distributed resource information can be selected from the researcher terminal (10) and created as selected distributed resource information.

[0057] In addition, after receiving a distributed resource response, the resource recommendation unit (102) can transmit a new distributed resource query corresponding to the distributed resource response to the researcher terminal (10) that transmitted the distributed resource response. Here, the new distributed resource query can be generated by considering the distributed resource query and the distributed resource response.

[0058] Additionally, the resource recommendation unit (102) can repeatedly transmit corresponding distributed resource queries and receive distributed resource responses to the distributed resource queries. Accordingly, the resource recommendation unit (102) can analyze multiple distributed resource queries and distributed resource responses to the multiple distributed resource queries to extract distributed resource information. The extracted distributed resource information can be used to generate selected distributed resource information.

[0059] In addition, the resource recommendation unit (102) can store grid model information. Here, the grid model information refers to information about a grid model that controls power supply by connecting distributed resources applied in the simulation system, and may include grid model type, grid model specifications, grid model contents, etc. In addition, the grid model type may include distribution, transmission, etc., the grid model specifications may indicate the scale of the grid model, and the grid model contents may include information about the grid model's operating logic, etc.

[0060] In addition, the resource recommendation unit (102) can transmit grid model information to the researcher terminal (10). Here, the resource recommendation unit (102) can transmit all of the plurality of grid model information stored to the researcher terminal (10). In addition, the researcher terminal (10) can receive and output the grid model information. Here, the researcher can select at least one grid model information through the researcher terminal (10), and the researcher terminal (10) can generate the at least one selected grid model information as selected grid model information and transmit the selected grid model information to the resource recommendation unit (102).

[0061] Meanwhile, the resource recommendation unit (102) can extract grid model information corresponding to the selected distributed resource information and generate a grid model query based on the extracted grid model information. Here, the grid model query may refer to a question necessary for selecting and determining grid model information, and may include, for example, "What do you want to do with the power of distributed resource A?"

[0062] The resource recommendation unit (102) can transmit a grid model query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the grid model query, and the researcher can input a grid model answer to the grid model query through the researcher terminal (10), and the researcher terminal (10) can transmit the grid model answer to the resource recommendation unit (102). In addition, the resource recommendation unit (102) can analyze the grid model query and the grid model answer to extract at least one piece of grid model information, and transmit the extracted grid model information to the researcher terminal (10). Here, the grid model answer is in natural language, and the resource recommendation unit (102) can perform natural language processing of the grid model answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the grid model answer. Additionally, the researcher can check the extracted grid model information through the researcher terminal (10), and at least one extracted grid model information can be selected from the researcher terminal (10) and generated as selected grid model information.

[0063] In addition, after receiving a grid model response, the resource recommendation unit (102) can transmit a new grid model query corresponding to the grid model response to the researcher terminal (10) that transmitted the grid model response. Here, the new grid model query can be generated by considering the grid model query and the grid model response.

[0064] In addition, the resource recommendation unit (102) can repeatedly transmit corresponding grid model queries and receive grid model responses to the grid model queries. Accordingly, the resource recommendation unit (102) can analyze multiple grid model queries and grid model responses to the multiple grid model queries to extract grid model information. The extracted grid model information can be used to generate selected grid model information.

[0065] The data function recommendation unit (103) can store data set information. Here, the data set information refers to information about a data set generated for an actual distributed resource applied to the simulation system, and may include data types, data collection periods, etc. In addition, the data types may include distributed resource operation data, distributed resource power generation data, distributed resource sensor data, weather data, etc., and the data collection period may refer to the period during which the data was collected.

[0066] In addition, the data function recommendation unit (103) can transmit data set information to the researcher terminal (10). Here, the data function recommendation unit (103) can transmit all of the plurality of data set information stored to the researcher terminal (10). In addition, the researcher terminal (10) can receive and output the data set information. Here, the researcher can select at least one data set information through the researcher terminal (10), and the researcher terminal (10) can generate the selected at least one data set information as selected data set information and transmit the selected data set information to the data function recommendation unit (103).

[0067] Meanwhile, the data function recommendation unit (103) can extract data set information corresponding to the selection grid model information and generate a data set query based on the extracted data set information. Here, the data set query may refer to a question necessary for selecting and determining data set information, and may include, for example, "What data do you want to apply?"

[0068] The data function recommendation unit (103) can transmit a data set query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the data set query, and the researcher can input a data set answer to the data set query through the researcher terminal (10), and the researcher terminal (10) can transmit the data set answer to the data function recommendation unit (103). In addition, the data function recommendation unit (103) can analyze the data set query and the data set answer to extract at least one data set information, and transmit the extracted data set information to the researcher terminal (10). Here, the data set answer is in natural language, and the data function recommendation unit (103) can perform natural language processing of the data set answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the data set answer. Additionally, the researcher can check the extracted data set information through the researcher terminal (10), and at least one extracted data set information can be selected from the researcher terminal (10) and generated as selected data set information.

[0069] In addition, after receiving a data set response, the data function recommendation unit (103) can transmit a new data set query corresponding to the data set response to the researcher terminal (10) that transmitted the distributed resource response. Here, the new data set query can be generated by considering the data set query and the data set response.

[0070] The data function recommendation unit (103) can repeatedly transmit corresponding data set queries and receive data set responses to the data set queries. As a result, the data function recommendation unit (103) can extract data set information by combining multiple data set queries and data set responses to the multiple data set queries. The extracted data set information can be used to generate selected data set information.

[0071] Additionally, the data function recommendation unit (103) can store function module information. Here, the function module information refers to information about function modules (e.g., APIs, code blocks, etc.) for processing, such as calculation, conversion, and analysis of data sets in the simulation system, and can include function module names, function module contents, etc. In addition, the function module contents can include function contents executed by the function module.

[0072] In addition, the data function recommendation unit (103) can transmit function module information to the researcher terminal (10). Here, the data function recommendation unit (103) can transmit all of the plurality of function module information stored to the researcher terminal (10). In addition, the researcher terminal (10) can receive and output the function module information. Here, the researcher can select at least one function module information through the researcher terminal (10), and the researcher terminal (10) can generate the at least one selected function module information as selected function module information and transmit the selected function module information to the data function recommendation unit (103).

[0073] Meanwhile, the data function recommendation unit (103) can extract function module information corresponding to the selected data set information and generate a function module query based on the extracted function module information. Here, the function module query may refer to a question necessary for selecting and determining function module information, and may include, for example, "What function do you want to apply?"

[0074] The data function recommendation unit (103) can transmit a function module query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the function module query, and the researcher can input a function module answer to the function module query through the researcher terminal (10), and the researcher terminal (10) can transmit the function module answer to the data function recommendation unit (103). In addition, the data function recommendation unit (103) can analyze the function module query and the function module answer to extract at least one function module information, and transmit the extracted function module information to the researcher terminal (10). Here, the function module answer is in natural language, and the data function recommendation unit (103) can perform natural language processing of the grid model answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the function module answer. Additionally, the researcher can check the extracted functional module information through the researcher terminal (10), and at least one extracted functional module information can be selected from the researcher terminal (10) and generated as selected functional module information.

[0075] In addition, after receiving a function module response, the data function recommendation unit (103) can transmit a new function module query corresponding to the function module response to the researcher terminal (10) that transmitted the function module response. Here, the new function module query can be generated by considering the function module query and the function module response.

[0076] The data function recommendation unit (103) can repeatedly transmit corresponding function module queries and receive function module responses to the function module queries. Accordingly, the data function recommendation unit (103) can analyze multiple function module queries and function module responses to the multiple function module queries to extract function module information. The extracted function module information can be used to generate selected function module information.

[0077] The virtual environment unit (104) can create a virtual environment. Here, the virtual environment can mean a simulation system corresponding to selected simulation type information, selected distributed resource information, selected grid module information, selected data set information, and selected function module information, and can be a virtual demonstration complex system that implements processing such as calculation, conversion, and analysis by using a data set according to selected data set information and a function module according to selected function module information.

[0078] In addition, the virtual environment unit (104) can calculate the data capacity that can process the data set according to the selected data set information in the simulation type according to the selected simulation type information, and can calculate the specifications of the hardware (e.g., CPU / GPU, memory, etc.) that can execute the function module according to the selected function module information. Here, the virtual environment unit (104) can create a virtual environment by setting up a cloud-based data storage based on the data capacity and a cloud-based server based on the hardware specifications. That is, the virtual environment can be composed of a data storage and server set by the virtual environment unit (104). Researchers can conduct research and development through a cloud-based virtual environment created by the virtual environment unit (104) through the researcher terminal (10).

[0079] Additionally, the virtual environment unit (104) can generate authentication information corresponding to the virtual environment and transmit the authentication information to the researcher terminal (10) corresponding to the virtual environment. The researcher terminal (10) can connect to the virtual environment by transmitting the received authentication information to the virtual environment unit (104), and the researcher can conduct research and development through simulations using the virtual environment. Furthermore, the authentication information can be valid for the entire research and development period, thereby enabling the researcher terminal (10) to utilize the virtual environment.

[0080] The usage analysis unit (105) can receive and store usage logs transmitted from the researcher terminal (10) by the researcher terminal (10), and generate analysis information based on the usage logs. Here, the usage logs are generated according to the operation of the virtual environment, but can be generated by the operation of the researcher terminal (10) connected to the virtual environment and the simulation results of the virtual environment.

[0081] For example, a researcher terminal (10) is connected to a virtual environment, and a simulation system according to selected simulation type information applies a data set according to selected data set information to distributed resources according to selected distributed resource information connected to a grid model according to selected grid model information, and controls distributed resources using a function module according to selected function module information, thereby implementing a simulation. Here, the operation of the virtual environment by the researcher terminal (10) and the simulation results of the virtual environment can be generated as a usage log. This usage log can be stored in the usage analysis unit (105).

[0082] The usage analysis unit (105) can generate analysis information by analyzing the interaction of distributed resources according to selected distributed resource information, grid models according to selected grid model information, data sets according to selected data set information, and functional modules according to selected functional module information based on the usage log.

[0083] Additionally, the usage analysis unit (105) can generate recommendation information based on the simulation type information based on the analysis information. Here, the recommendation information may refer to information about an algorithm that can extract distributed resource information, grid module information, data set information, and functional module information suitable for each simulation type information. This recommendation information may be continuously updated based on the analysis information. As a result, the recommendation information can match the optimal distributed resource information, grid module information, data set information, and functional module information to the simulation type information.

[0084] The energy simulation component recommendation system (100) according to the present embodiment transmits simulation type information to the researcher's researcher terminal (10) through the type recommendation unit (101), distributed resource information and grid model information through the resource recommendation unit (102), and data set information and function module information through the data function recommendation unit (103), and allows the researcher to select the simulation type information, distributed resource information, grid model information, data set information, and function module information transmitted through the researcher terminal (10). Here, the selected simulation type information, distributed resource information, grid model information, data set information, and function module information can be used as a basis for creating a virtual environment for research and development. That is, the researcher can receive and use an environment, which is a simulation system, by selecting the simulation type information, distributed resource information, grid model information, data set information, and function module information. Therefore, the energy simulation component recommendation system (100) according to the present embodiment allows the best components and data for energy technology research and development through simulation to be easily selected and used.

[0085] In addition, the energy simulation component recommendation system (100) according to the present embodiment can transmit the extracted simulation type information, distributed resource information, grid model information, data set information, and function module information to the researcher terminal (10) in the form of a dialogue through questions and answers with the researcher when transmitting simulation type information through the type recommendation unit (101), transmitting distributed resource information and grid model information through the resource recommendation unit (102), and transmitting data set information and function module information through the data function recommendation unit (103). In addition, the simulation type information, distributed resource information, grid model information, data set information, and function module information can be combined and linked with each other. A virtual environment can be created by combining the above-described simulation type information, distributed resource information, grid model information, data set information, and function module information. Therefore, the energy simulation component recommendation system (100) according to the present embodiment can provide the best virtual environment for research and development and enable the creation of improved research results.

[0086] In addition, the energy simulation component recommendation system (100) according to the present embodiment allows components for simulation according to research and development to be combined with each other through selection, thereby shortening the time required for research and development and enabling implementation of intensive research and development.

[0087] FIG. 2 is a flowchart illustrating a method for recommending energy simulation components according to one embodiment of the present invention.

[0088] The energy simulation component recommendation method according to one embodiment of the present invention illustrated in FIG. 2 recommends simulation type information, distributed resource information, grid model information, data set information, and function module information to a researcher, creates a virtual environment through a combination of simulation type information, distributed resource information, grid model information, data set information, and function module information selected by the researcher, and performs energy-related simulation through the virtual environment. The energy simulation component recommendation method of this embodiment will be described using the energy simulation component recommendation system (100) mentioned above.

[0089] First, a step (S101) may be performed in which the type recommendation unit (101) transmits stored simulation type information to the researcher terminal (10), and the selected simulation type information is received according to the selection of the simulation type information transmitted to the researcher terminal (10). Here, the simulation type information refers to information about a simulation system, which is a virtual demonstration complex system for energy-related research and development, and may include a simulation type, a type description, etc. In addition, the simulation type refers to a name according to the type of simulation system, and may include a distributed resource-based power system, a microgrid system, an integrated power plant system, a virtual power plant (VPP) system, an energy trading system, a V2G (vehicle to grid) system, etc., and the type description may include content about the simulation system according to the simulation type. In the present embodiment, the simulation type information may be configured in multiple pieces according to the simulation type.

[0090] In step S101, the type recommendation unit (101) transmits simulation type information to the researcher terminal (10), but can transmit all of the stored multiple simulation type information to the researcher terminal (10).

[0091] Meanwhile, when a researcher wants to conduct a simulation through a virtual environment by an energy simulation component system (100), the researcher can transmit a desired signal to the type recommendation unit (101) through the researcher terminal (10). When the type recommendation unit (101) has received the desired signal, in step S101, the type recommendation unit (101) can transmit simulation type information to the researcher terminal (10) that transmitted the desired signal.

[0092] In step S101, the researcher terminal (10) can receive and output simulation type information. Here, the researcher can select at least one piece of simulation type information through the researcher terminal (10), and the researcher terminal (10) can generate the selected at least one piece of simulation type information as selected simulation type information and transmit the selected simulation type information to the type recommendation unit (101).

[0093] Meanwhile, in step S101, the type recommendation unit (101) can generate a simulation query based on simulation type information. Here, the simulation query may refer to a question necessary for selecting and determining simulation type information, and may include, for example, "What is your research topic?", "Where is your research-related institution?", "Where is your research target region?", etc. In addition, the type recommendation unit (101) can transmit the simulation query to the researcher terminal (10) that transmitted the aforementioned request signal.

[0094] In the above S101 step, the type recommendation unit (101) can transmit a simulation query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the simulation query, and the researcher can input a simulation answer to the simulation query through the researcher terminal (10), and the researcher terminal (10) can transmit the simulation answer to the type recommendation unit (101). In addition, the type recommendation unit (101) can analyze the simulation query and the simulation answer to extract at least one piece of simulation type information, and transmit the extracted simulation type information to the researcher terminal (10). Here, the simulation answer is in natural language, and the type recommendation unit (101) can perform natural language processing of the simulation answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the simulation answer. Additionally, the researcher can check the extracted simulation type information through the researcher terminal (10), and at least one extracted simulation type information can be selected from the researcher terminal (10) and generated as the selected simulation type information.

[0095] Additionally, in step S101, after receiving a simulation answer, the type recommendation unit (101) can transmit a new simulation query corresponding to the simulation answer to the researcher terminal (10) that transmitted the simulation answer. Here, the new simulation query can be generated by considering the simulation query and the simulation answer.

[0096] In step S101 as described above, the type recommendation unit (101) can repeatedly transmit corresponding simulation queries and receive simulation responses to the simulation queries. Accordingly, the type recommendation unit (101) can analyze multiple simulation queries and simulation responses to the multiple simulation queries to extract simulation type information. The extracted simulation type information can be used to generate selected simulation type information.

[0097] Next, a step (S102) may be performed in which the resource recommendation unit (102) transmits the stored distributed resource information to the researcher terminal (10), and the selected distributed resource information is transmitted according to the selection of the distributed resource information transmitted to the researcher terminal (10). Here, the distributed resource information refers to information on the distributed resource applied in the simulation system, and may include the type of distributed resource, the location of the distributed resource, the capacity of the distributed resource, etc. In addition, the type of distributed resource may include fuel cells, liquefied natural gas gasification, hydrogen energy generation, geothermal power generation, bio power generation, wave power generation, hydroelectric power generation, wind power generation, waste power generation, solar power generation, solar power generation, etc., and the location of the distributed resource may include the latitude and longitude of the installation location of the distributed resource, and the capacity of the distributed resource may be a numerical value indicating the size of the distributed resource. In the present embodiment, the distributed resource information may include the location of the distributed resource and the capacity of the distributed resource for each type of distributed resource.

[0098] In step S102, the resource recommendation unit (102) transmits distributed resource information to the researcher terminal (10), and may transmit all of the stored multiple pieces of distributed resource information to the researcher terminal (10). In addition, the researcher terminal (10) may receive and output the distributed resource information. Here, the researcher may select at least one piece of distributed resource information through the researcher terminal (10), and the researcher terminal (10) may generate the selected at least one piece of distributed resource information as selected distributed resource information and transmit the selected distributed resource information to the resource recommendation unit (102).

[0099] Meanwhile, in step S102, the resource recommendation unit (102) can extract distributed resource information corresponding to the selected simulation type information and generate a distributed resource query based on the extracted distributed resource information. Here, the distributed resource query may refer to a question necessary for selecting and deciding on distributed resource information, and may include, for example, "What distributed resource do you want to use?", "Where do you want to install the distributed resource?", and "What is the scale of your distributed resource?"

[0100] In step S102 as described above, the resource recommendation unit (102) can transmit a distributed resource query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the distributed resource query, and the researcher can input a distributed resource answer to the distributed resource query through the researcher terminal (10), and the researcher terminal (10) can transmit the distributed resource answer to the resource recommendation unit (102). In addition, the resource recommendation unit (102) can analyze the distributed resource query and the distributed resource answer to extract at least one piece of distributed resource information, and transmit the extracted distributed resource information to the researcher terminal (10). Here, the distributed resource answer is in natural language, and the resource recommendation unit (102) can perform natural language processing of the distributed resource answer using artificial intelligence, and the researcher terminal (10) can mean the researcher terminal that transmitted the distributed resource answer. In addition, the researcher can check the extracted distributed resource information through the researcher terminal (10), and at least one extracted distributed resource information can be selected from the researcher terminal (10) and created as selected distributed resource information.

[0101] Additionally, in step S102, after receiving a distributed resource response, the resource recommendation unit (102) can transmit a new distributed resource query corresponding to the distributed resource response to the researcher terminal (10) that transmitted the distributed resource response. Here, the new distributed resource query can be generated by considering the distributed resource query and the distributed resource response.

[0102] In step S102 as described above, the resource recommendation unit (102) can repeatedly transmit corresponding distributed resource queries and receive distributed resource responses to the distributed resource queries. Accordingly, the resource recommendation unit (102) can analyze multiple distributed resource queries and distributed resource responses to the multiple distributed resource queries to extract distributed resource information. The extracted distributed resource information can be used to generate selected distributed resource information.

[0103] Next, a step (S103) may be performed in which the resource recommendation unit (102) transmits the stored grid model information to the researcher terminal (10), and selects grid model information according to the selection of the grid model information transmitted to the researcher terminal (10). Here, the grid model information refers to information about a grid model that controls power supply by connecting distributed resources applied in the simulation system, and may include a grid model type, a grid model specification, a grid model description, etc. In addition, the grid model type may include distribution, transmission, etc., the grid model specification may indicate the scale of the grid model, and the grid model description may include information about the operation logic of the grid model, etc.

[0104] In step S103, the resource recommendation unit (102) transmits grid model information to the researcher terminal (10), and may transmit all of the plurality of grid model information stored to the researcher terminal (10). In addition, the researcher terminal (10) may receive and output the grid model information. Here, the researcher may select at least one grid model information through the researcher terminal (10), and the researcher terminal (10) may generate the selected at least one grid model information as selected grid model information and transmit the selected grid model information to the resource recommendation unit (102).

[0105] Meanwhile, in step S103, the resource recommendation unit (102) can extract grid model information corresponding to the selected distributed resource information and generate a grid model query based on the extracted grid model information. Here, the grid model query may refer to a question necessary for selecting and determining grid model information, and may include, for example, "What do you want to do with the power of distributed resource A?"

[0106] In step S103 as described above, the resource recommendation unit (102) can transmit a grid model query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the grid model query, and the researcher can input a grid model answer to the grid model query through the researcher terminal (10), and the researcher terminal (10) can transmit the grid model answer to the resource recommendation unit (102). In addition, the resource recommendation unit (102) can analyze the grid model query and the grid model answer to extract at least one piece of grid model information, and transmit the extracted grid model information to the researcher terminal (10). Here, the grid model answer is in natural language, and the resource recommendation unit (102) can perform natural language processing of the grid model answer using artificial intelligence, and the researcher terminal (10) can refer to the researcher terminal that transmitted the grid model answer. Additionally, the researcher can check the extracted grid model information through the researcher terminal (10), and at least one extracted grid model information can be selected from the researcher terminal (10) and generated as selected grid model information.

[0107] Additionally, in step S103, after receiving the grid model answer, the resource recommendation unit (102) can transmit a new grid model query corresponding to the grid model answer to the researcher terminal (10) that transmitted the grid model answer. Here, the new grid model query can be generated by considering the grid model query and the grid model answer.

[0108] In step S103 as described above, the resource recommendation unit (102) can repeatedly transmit corresponding grid model queries and receive grid model responses to the grid model queries. Accordingly, the resource recommendation unit (102) can analyze multiple grid model queries and grid model responses to the multiple grid model queries to extract grid model information. The extracted grid model information can be used to generate selected grid model information.

[0109] Next, a step (S104) may be performed in which the data function recommendation unit (103) transmits stored data set information to the researcher terminal (10), and selects data set information according to the selection of the data set information transmitted to the researcher terminal (10). Here, the data set information refers to information about a data set generated for an actual distributed resource applied to the simulation system, and may include a data type, a data collection period, etc. In addition, the data type may include operation data of the distributed resource, power generation data of the distributed resource, sensor data of the distributed resource, weather data, etc., and the data collection period may refer to a period in which the data was collected.

[0110] In step S104, the data function recommendation unit (103) transmits the data set information to the researcher terminal (10), and can transmit all of the stored multiple data set information to the researcher terminal (10). In addition, the researcher terminal (10) can receive and output the data set information. Here, the researcher can select at least one data set information through the researcher terminal (10), and the researcher terminal (10) can generate the selected at least one data set information as selected data set information and transmit the selected data set information to the data function recommendation unit (103).

[0111] Meanwhile, in step S104, the data function recommendation unit (103) can extract data set information corresponding to the selected grid model information and generate a data set query based on the extracted data set information. Here, the data set query may refer to a question necessary for selecting and determining data set information, and may include, for example, "What data do you want to apply?"

[0112] In step S104 as described above, the data function recommendation unit (103) can transmit a data set query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the data set query, and the researcher can input a data set answer to the data set query through the researcher terminal (10), and the researcher terminal (10) can transmit the data set answer to the data function recommendation unit (103). In addition, the data function recommendation unit (103) can analyze the data set query and the data set answer to extract at least one data set information, and transmit the extracted data set information to the researcher terminal (10). Here, the data set answer is in natural language, and the data function recommendation unit (103) can perform natural language processing of the data set answer using artificial intelligence, and the researcher terminal (10) can mean the researcher terminal that transmitted the data set answer. Additionally, the researcher can check the extracted data set information through the researcher terminal (10), and at least one extracted data set information can be selected from the researcher terminal (10) and generated as selected data set information.

[0113] Additionally, in step S104, after receiving the data set response, the data function recommendation unit (103) can transmit a new data set query corresponding to the data set response to the researcher terminal (10) that transmitted the distributed resource response. Here, the new data set query can be generated by considering the data set query and the data set response.

[0114] In step S104 as described above, the data function recommendation unit (103) can repeatedly transmit corresponding data set queries and receive data set responses to the data set queries. As a result, the data function recommendation unit (103) can extract data set information by combining multiple data set queries and data set responses to the multiple data set queries. The extracted data set information can be used to generate selected data set information.

[0115] Next, a step (S105) may be performed in which the data function recommendation unit (103) transmits stored function module information to the researcher terminal (10), and selects function module information according to the selection of the function module information transmitted to the researcher terminal (10). Here, the function module information refers to information about a function module (e.g., API, code block, etc.) for processing, such as calculation, conversion, and analysis of a data set in a simulation system, and may include a function module name, function module content, etc. In addition, the function module content may include function content executed by the function module.

[0116] In step S105, the data function recommendation unit (103) transmits the function module information to the researcher terminal (10), and can transmit all of the stored multiple function module information to the researcher terminal (10). In addition, the researcher terminal (10) can receive and output the function module information. Here, the researcher can select at least one function module information through the researcher terminal (10), and the researcher terminal (10) can generate the selected at least one function module information as selected function module information and transmit the selected function module information to the data function recommendation unit (103).

[0117] Meanwhile, in step S105, the data function recommendation unit (103) can extract function module information corresponding to the selected data set information and generate a function module query based on the extracted function module information. Here, the function module query may refer to a question necessary for selecting and determining function module information, and may include, for example, "What function do you want to apply?"

[0118] In step S105 as described above, the data function recommendation unit (103) can transmit a function module query to the researcher terminal (10). Here, the researcher terminal (10) can receive and output the function module query, and the researcher can input a function module answer to the function module query through the researcher terminal (10), and the researcher terminal (10) can transmit the function module answer to the data function recommendation unit (103). In addition, the data function recommendation unit (103) can analyze the function module query and the function module answer to extract at least one function module information, and transmit the extracted function module information to the researcher terminal (10). Here, the function module answer is in natural language, and the data function recommendation unit (103) can perform natural language processing of the grid model answer using artificial intelligence, and the researcher terminal (10) can mean the researcher terminal that transmitted the function module answer. Additionally, the researcher can check the extracted functional module information through the researcher terminal (10), and at least one extracted functional module information can be selected from the researcher terminal (10) and generated as selected functional module information.

[0119] Additionally, in step S105, after receiving a function module response, the data function recommendation unit (103) can transmit a new function module query corresponding to the function module response to the researcher terminal (10) that transmitted the function module response. Here, the new function module query can be generated by considering the function module query and the function module response.

[0120] In step S105 as described above, the data function recommendation unit (103) can repeatedly transmit corresponding function module queries and receive function module responses to the function module queries. As a result, the data function recommendation unit (103) can analyze multiple function module queries and function module responses to the multiple function module queries to extract function module information. The extracted function module information can be used to generate selected function module information.

[0121] Next, a step (S106) may be performed in which the virtual environment unit (104) creates a virtual environment. Here, the virtual environment may mean a simulation system corresponding to the selected simulation type information, the selected distributed resource information, the selected grid module information, the selected data set information, and the selected function module information, and may be a virtual demonstration complex system that implements processing such as calculation, conversion, and analysis by using a data set according to the selected data set information and a function module according to the selected function module information.

[0122] In addition, in step S106, the virtual environment unit (104) can calculate the data capacity that can process the data set according to the selected data set information in the simulation type according to the selected simulation type information, and can calculate the specifications of the hardware (e.g., CPU / GPU, memory, etc.) that can execute the function module according to the selected function module information. Here, the virtual environment unit (104) can create a virtual environment by setting up a cloud-based data storage based on the data capacity and a cloud-based server based on the hardware specifications. That is, the virtual environment can be composed of a data storage and server set by the virtual environment unit (104). A researcher can conduct research and development through a cloud-based virtual environment created by the virtual environment unit (104) through a researcher terminal (10).

[0123] Additionally, in step S106, the virtual environment unit (104) can generate authentication information corresponding to the virtual environment and transmit the authentication information to the researcher terminal (10) corresponding to the virtual environment. The researcher terminal (10) can connect to the virtual environment by transmitting the received authentication information to the virtual environment unit (104), and the researcher can conduct research and development through simulations using the virtual environment. In addition, the authentication information can be valid during the research and development period, thereby enabling the use of the virtual environment by the researcher terminal (10).

[0124] Next, a step (S107) may be performed in which the usage analysis unit (105) receives usage logs transmitted from the researcher terminal (10) by the researcher terminal (10) and generates analysis information based on the usage logs. Here, the usage logs are generated according to the operation of the virtual environment, but may be generated by the operation of the researcher terminal (10) connected to the virtual environment and the simulation results of the virtual environment.

[0125] For example, a researcher terminal (10) is connected to a virtual environment, and a simulation system according to selected simulation type information applies a data set according to selected data set information to distributed resources according to selected distributed resource information connected to a grid model according to selected grid model information, and controls distributed resources using a function module according to selected function module information, thereby implementing a simulation. Here, the operation of the virtual environment by the researcher terminal (10) and the simulation results of the virtual environment can be generated as a usage log. This usage log can be stored in the usage analysis unit (105).

[0126] In step S107 as described above, the usage analysis unit (105) can generate analysis information by analyzing the interaction of distributed resources according to selected distributed resource information, grid models according to selected grid model information, data sets according to selected data set information, and function modules according to selected function module information based on the usage log.

[0127] Additionally, at step S107, the usage analysis unit (105) can generate recommendation information according to simulation type information based on the analysis information. Here, the recommendation information may refer to information about an algorithm that can extract distributed resource information, grid module information, data set information, function module information, etc. suitable for each simulation type information. This recommendation information may be continuously updated based on the analysis information. As a result, the recommendation information can correspond to the best distributed resource information, grid module information, data set information, function module information, etc. for the simulation type information.

[0128] The energy simulation component recommendation method according to the present embodiment transmits simulation type information to the researcher's researcher terminal (10) through the type recommendation unit (101), distributed resource information and grid model information through the resource recommendation unit (102), and data set information and function module information through the data function recommendation unit (103), and allows the researcher to select the simulation type information, distributed resource information, grid model information, data set information, and function module information transmitted through the researcher terminal (10). Here, the selected simulation type information, distributed resource information, grid model information, data set information, and function module information can be used as a basis for creating a virtual environment for research and development. That is, the researcher can receive and use an environment, which is a simulation system, by selecting the simulation type information, distributed resource information, grid model information, data set information, and function module information. Therefore, the energy simulation component recommendation method according to the present embodiment allows the best components and data for energy technology research and development through simulation to be easily selected and used.

[0129] In addition, the energy simulation component recommendation method according to the present embodiment can transmit the extracted simulation type information, distributed resource information, grid model information, data set information, and function module information to the researcher terminal (10) in the form of a dialogue through questions and answers with the researcher in the transmission of simulation type information through the type recommendation unit (101), distributed resource information and grid model information through the resource recommendation unit (102), and data set information and function module information through the data function recommendation unit (103). In addition, the simulation type information, distributed resource information, grid model information, data set information, and function module information can be combined and linked with each other. A virtual environment can be created by combining the above-described simulation type information, distributed resource information, grid model information, data set information, and function module information. Therefore, the energy simulation component recommendation method according to the present embodiment can provide the best virtual environment for research and development and enable the generation of improved research results.

[0130] In addition, the method for recommending energy simulation components according to the present embodiment allows components for simulation according to research and development to be combined with each other through selection, thereby shortening the time required for research and development and enabling implementation of intensive research and development.

[0131] The functional operations described in this specification and the embodiments of the present subject matter can be implemented in digital electronic circuits, computer software, firmware, or hardware, or in a combination of one or more of these, including the structures disclosed herein and their structural equivalents.

[0132] Embodiments of the subject matter described herein may be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a tangible program medium for execution by or controlling the operation of a data processing device. The tangible program medium may be a radio signal or a computer-readable medium. A radio signal is an artificially generated signal, such as a machine-generated electrical, optical, or electromagnetic signal, that is generated to encode information for transmission to a suitable receiver device for execution by a computer. The computer-readable medium may be a machine-readable storage device, a machine-readable storage substrate, a memory device, a combination of materials that affect a machine-readable radio signal, or a combination of one or more of these.

[0133] A computer program (also known as a program, software, software application, script or code) may be written in any programming language, including compiled or interpreted languages, a priori or procedural languages, and may be deployed in any form, including as a standalone program, a module, a component, a subroutine or other unit suitable for use in a computing environment.

[0134] Computer programs do not necessarily correspond to files in a file system. A program may be stored within a single file provided to the requested program, within multiple interacting files (e.g., a file storing one or more modules, subprograms, or portions of code), or within a file containing other programs or data (e.g., one or more scripts stored within a markup language document).

[0135] A computer program may be deployed to run on a single computer or on multiple computers located at a single site or distributed across multiple sites and interconnected by a communications network.

[0136] Additionally, the logical flow and structural block diagrams described herein describe corresponding functions and corresponding acts and / or specific methods supported by the disclosed structural means, and can also be used to construct corresponding software structures and algorithms and their equivalents.

[0137] The processes and logic flows described herein are executable by one or more programmable processors executing one or more computer programs to perform functions by operating on input data and generating output.

[0138] Processors suitable for executing computer programs include, for example, general-purpose and special-purpose microprocessors, as well as any one or more processors of any type of digital computer. Typically, the processor will receive instructions and data from read-only memory, random-access memory, or both.

[0139] The core elements of a computer are one or more memory devices for storing instructions and data, and a processor for executing instructions. Additionally, a computer will typically be coupled to or include one or more mass storage devices, such as magnetic, magneto-optical, or optical disks, to receive data from, transfer data to, or both of these operations. However, a computer need not include such devices.

[0140] This description presents the best mode of the invention and provides examples to illustrate the invention and to enable those skilled in the art to make and use the invention. The specification, as written, is not intended to limit the invention to the specific terms set forth herein.

[0141] Accordingly, while the present invention has been described in detail with reference to the above-described examples, those skilled in the art will appreciate that modifications, variations, and variations can be made to these examples without departing from the scope of the present invention. In short, it is to be understood that to achieve the intended effects of the present invention, not all functional blocks depicted in the drawings must be separately included, nor must all orders depicted in the drawings be followed in the exact order depicted. Even if this is not the case, the technical scope of the present invention as set forth in the claims may still be encompassed.

[0142] [Explanation of symbols]

[0143] 101: Energy Simulation Component Recommendation System

[0144] 101: Type Recommendation

[0145] 102: Resource Recommendation Department

[0146] 103: Data Feature Recommendation

[0147] 104: Virtual Environment

[0148] 105: Usage Analysis Department

Claims

1. In the energy simulation component recommendation system connected to the researcher terminal and network, A type recommendation unit that stores simulation type information, transmits simulation type information to a researcher terminal, and receives selected simulation type information from the researcher terminal according to the selection of simulation type information transmitted to the researcher terminal; A resource recommendation unit that stores distributed resource information and grid model information, transmits the distributed resource information and grid model information to a researcher terminal, and receives selected distributed resource information according to the selection of the distributed resource information transmitted to the researcher terminal and selected grid model information according to the selection of the grid model information transmitted to the researcher terminal from the researcher terminal; A data function recommendation unit that stores data set information and function module information, transmits data set information and function module information to a researcher terminal, and receives selected data set information according to selection of data set information transmitted to the researcher terminal and selected function module information according to selection of function module information transmitted to the researcher terminal from the researcher terminal; A virtual environment section that creates a virtual environment based on selected simulation type information, selected distributed resource information, selected grid model information, selected data set information, and selected function module information; and An energy simulation component recommendation system characterized by including a usage analysis unit that receives and stores usage logs transmitted from a researcher terminal, generates analysis information according to the usage logs, and generates recommendation information according to simulation type information based on the analysis information.

2. In paragraph 1, Simulation type information includes simulation type and type content, Distributed resource information includes distributed resource type, distributed resource location, and distributed resource capacity, and grid model information includes grid model type, grid model specification, and grid model content. An energy simulation component recommendation system characterized in that the data set information includes data type and data collection period, and the functional module information includes module name and functional module contents.

3. In paragraph 2, The type recommendation section generates a simulation query corresponding to the simulation type information. An energy simulation component recommendation system characterized in that the type recommendation unit transmits a simulation query to a researcher terminal, receives a simulation answer in natural language form for the simulation query from the researcher terminal, performs natural language processing on the simulation answer, analyzes the simulation query and the simulation answer to extract at least one simulation type information, and transmits the extracted simulation type information to the researcher terminal that transmitted the simulation answer.

4. In paragraph 2, The resource recommendation unit extracts distributed resource information corresponding to the selected simulation type information and generates a distributed resource query corresponding to the extracted distributed resource information. An energy simulation component recommendation system characterized in that the resource recommendation unit transmits a distributed resource query to a researcher terminal, receives a distributed resource response in natural language form for the distributed resource query from the researcher terminal, processes the distributed resource response in natural language, analyzes the distributed resource query and the distributed resource response to extract at least one piece of distributed resource information, and transmits the extracted distributed resource information to the researcher terminal that transmitted the distributed resource response.

5. In paragraph 4, The resource recommendation unit extracts grid model information corresponding to the selected distributed resource information and generates a grid model query corresponding to the extracted grid model information. An energy simulation component recommendation system characterized in that the resource recommendation unit transmits a grid model query to a researcher terminal, receives a grid model response in natural language form for the grid model query from the researcher terminal, processes the grid model response in natural language, analyzes the grid model query and the grid model response to extract at least one piece of grid model information, and transmits the extracted grid model information to the researcher terminal that transmitted the grid model response.

6. In paragraph 2, The data function recommendation unit extracts data set information corresponding to the selected distributed resource information and the selected grid model information, and generates a data set query corresponding to the extracted data set information. An energy simulation component recommendation system characterized in that a data function recommendation unit transmits a data set query to a researcher terminal, receives a data set response in natural language form for the data set query from the researcher terminal, performs natural language processing on the data set response, analyzes the data set query and the data set response to extract at least one data set information, and transmits the extracted data set information to the researcher terminal that transmitted the data set response.

7. In paragraph 6, The data feature recommendation unit extracts feature module information corresponding to the selected data set information and generates a feature module query corresponding to the extracted feature module information. An energy simulation component recommendation system characterized in that the data function recommendation unit transmits a function module query to a researcher terminal, receives a function module response in natural language form in response to the function module query from the researcher terminal, performs natural language processing on the function module response, analyzes the function module query and the function module response to extract at least one function module information, and transmits the extracted function module information to the researcher terminal that transmitted the function module response.

8. In paragraph 2, An energy simulation component recommendation system characterized in that the virtual environment unit calculates the data capacity that can process the data set according to the selected data set information in the simulation type according to the selected simulation type information, calculates the specifications of the hardware that can execute the function module according to the selected function module information, and creates a virtual environment by setting up a cloud-based data storage based on the data capacity and a cloud-based server based on the specifications of the hardware.

9. In paragraph 2, When the researcher's terminal is connected to the virtual environment and a simulation is performed in the virtual environment, the researcher's terminal generates a usage log and transmits it to the usage analysis unit for storage. An energy simulation component recommendation system characterized in that the usage analysis unit generates analysis information by analyzing the interaction of distributed resources according to selected distributed resource information, grid models according to selected grid model information, data sets according to selected data set information, and functional modules according to selected functional module information based on usage logs. 10.(a) A step of transmitting simulation type information stored in the type recommendation section to the researcher terminal, and receiving selected simulation type information according to the selection of the simulation type information transmitted to the researcher terminal from the researcher terminal; (b) A step of transmitting the distributed resource information stored in the resource recommendation section to the researcher terminal, and receiving the selected distributed resource information according to the selection of the distributed resource information transmitted to the researcher terminal from the researcher terminal; (c) A step of transmitting grid model information stored in the resource recommendation section to a researcher terminal, and receiving selected grid model information according to the selection of grid model information transmitted to the researcher terminal from the researcher terminal; (d) A step of transmitting the stored data set information in the data function recommendation section to the researcher terminal, and receiving the selected data set information according to the selection of the data set information transmitted to the researcher terminal from the researcher terminal; (e) A step of transmitting function module information stored in the data function recommendation section to the researcher terminal, and receiving selected function module information according to the selection of function module information transmitted to the researcher terminal from the researcher terminal; (f) a step of creating a virtual environment based on the selected simulation type information, selected distributed resource information, selected grid model information, selected data set information, and selected function module information; and (g) A method for recommending energy simulation components, characterized in that it includes a step of the usage analysis unit receiving and storing usage logs transmitted from the researcher terminal, generating analysis information according to the usage logs, and generating recommendation information according to simulation type information based on the analysis information.

11. In paragraph 10, Simulation type information includes simulation type and type content, Distributed resource information includes distributed resource type, distributed resource location, and distributed resource capacity, and grid model information includes grid model type, grid model specification, and grid model content. A method for recommending energy simulation components, characterized in that the data set information includes data type and data collection period, and the function module information includes module name and function module contents.

12. In paragraph 11, in step (a), The type recommendation section generates a simulation query corresponding to the simulation type information, An energy simulation component recommendation method characterized in that a type recommendation unit transmits a simulation query to a researcher terminal, receives a simulation answer in natural language form for the simulation query from the researcher terminal, performs natural language processing on the simulation answer, analyzes the simulation query and the simulation answer to extract at least one simulation type information, and transmits the extracted simulation type information to the researcher terminal that transmitted the simulation answer.

13. In step (b) of paragraph 11, The resource recommendation unit extracts distributed resource information corresponding to the selected simulation type information and generates a distributed resource query corresponding to the extracted distributed resource information. A method for recommending energy simulation components, characterized in that the resource recommendation unit transmits a distributed resource query to a researcher terminal, receives a distributed resource response in natural language form for the distributed resource query from the researcher terminal, processes the distributed resource response in natural language, analyzes the distributed resource query and the distributed resource response to extract at least one piece of distributed resource information, and transmits the extracted distributed resource information to the researcher terminal that transmitted the distributed resource response.

14. In the 13th paragraph, in step (c), The resource recommendation unit extracts grid model information corresponding to the selected distributed resource information and generates a grid model query corresponding to the extracted grid model information. An energy simulation component recommendation method characterized in that a resource recommendation unit transmits a grid model query to a researcher terminal, receives a grid model response in natural language form for the grid model query from the researcher terminal, performs natural language processing on the grid model response, analyzes the grid model query and the grid model response to extract at least one piece of grid model information, and transmits the extracted grid model information to the researcher terminal that transmitted the grid model response.

15. In step (d) of paragraph 11, The data function recommendation unit extracts data set information corresponding to the selected distributed resource information and the selected grid model information, and generates a data set query corresponding to the extracted data set information. An energy simulation component recommendation method characterized in that a data function recommendation unit transmits a data set query to a researcher terminal, receives a data set response in natural language form for the data set query from the researcher terminal, performs natural language processing on the data set response, analyzes the data set query and the data set response to extract at least one data set information, and transmits the extracted data set information to the researcher terminal that transmitted the data set response.

16. In paragraph 15, in step (e), Extracts function module information corresponding to the data set information of the data feature recommendation booklet, and generates a function module query corresponding to the extracted function module information. A method for recommending energy simulation components, characterized in that the data function recommendation unit transmits a function module query to a researcher terminal, receives a function module response in natural language form in response to the function module query from the researcher terminal, performs natural language processing on the function module response, analyzes the function module query and the function module response to extract at least one function module information, and transmits the extracted function module information to the researcher terminal that transmitted the function module response.

17. In step (f) of paragraph 11, A method for recommending energy simulation components characterized in that the virtual environment unit calculates the data capacity that can process the data set according to the selected data set information in the simulation type according to the selected simulation type information, calculates the specifications of the hardware that can execute the function module according to the selected function module information, and creates a virtual environment by setting up a cloud-based data storage based on the data capacity and a cloud-based server based on the specifications of the hardware.

18. In step (g) of paragraph 11, When the researcher's terminal is connected to the virtual environment and a simulation is performed in the virtual environment, the researcher's terminal generates a usage log and transmits it to the usage analysis unit for storage. A method for recommending energy simulation components, characterized in that the usage analysis unit generates analysis information by analyzing the interaction of distributed resources according to selected distributed resource information, grid models according to selected grid model information, data sets according to selected data set information, and functional modules according to selected functional module information based on usage logs.

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