Rural energy revolution digital twinborn modeling system based on cloud edge collaboration

Abstract

The invention provides a rural energy revolution digital twin modeling system based on cloud edge collaboration. The rural energy revolution digital twin modeling system comprises a front-end graphical unit at least composed of a user interface unit, a digital twin core unit and a front-end event total scheduling unit. And the cloud system at least consists of a cloud edge collaboration module, a monomer modeling module, a topology management module and a digital twin modeling module. According to the invention, the transparency of energy use and the scientificity of optimization decision can be improved, and the intelligent and refined management of a rural energy system is promoted.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology combining cloud computing and edge computing, and more specifically, to a rural energy revolution digital twin modeling system based on cloud-edge collaboration. Background Art

[0002] As an emerging technical means, digital twin technology also faces challenges in data acquisition, processing and real-time communication during its implementation. Digital twin models need to rely on a large amount of real-time data to maintain their accuracy and dynamics, which requires high-speed data transmission and processing capabilities. In addition, the lightweight of the model is also one of the key issues. When the number of models and the amount of data become huge, how to ensure the scalability and efficient operation of the system is a problem that needs to be solved. The development of digital twin technology requires the coordination of technologies in different fields, including cloud computing, edge computing, the Internet of Things, etc., to achieve wider applications and more efficient performance.

[0003] Cloud-edge collaboration in edge computing systems is the key to achieving efficient data processing and application deployment. In the cloud-edge collaboration architecture, the Kubernetes control node serves as the control center of the cloud part, while KubeEdge serves as the edge computing solution, synchronizing instructions and status information between the cloud and the edge through CloudCore and EdgeCore. This architecture allows the cloud center to manage edge nodes like ordinary nodes, while EdgeCore executes cloud computing orchestration containerized applications on edge nodes to adapt to the characteristics of edge environments, such as limited resources and unstable networks.

[0004] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the prior art: the existing rural energy revolution digital twin modeling system usually lacks an effective cloud-edge collaboration mechanism, which limits the system's response speed and data processing capabilities, especially in rural environments with limited resources and unstable networks. In addition, the digital twin core unit in the prior art has limited functions and is difficult to meet diverse modeling needs. There are also bottlenecks in the interaction and data flow between the monomer modeling module, the topology management module, and the digital twin modeling module, which affects the efficiency and accuracy of the overall system. Summary of the invention

[0005] The present invention provides a rural energy revolution digital twin modeling system based on cloud-edge collaboration, including:

[0006] A front-end graphical unit consisting of at least a user interface unit, a digital twin core unit and a front-end event general scheduling unit, wherein the user interface unit is used to interact with the user, receive parameters input by the user and provide the user with digital twin modeling;

[0007] The digital twin core unit is used to store a variety of functional functions related to digital twin modeling operations, and the various functional functions can support the user's digital twin modeling operations;

[0008] The front-end event general scheduling unit is used to receive various operation information of the user and call corresponding function to respond to the user's operation;

[0009] A cloud-based system consisting of at least a cloud-edge collaboration module, a monomer modeling module, a topology management module and a digital twin modeling module, wherein the cloud-edge collaboration module is used to receive data requests sent by the front-end graphical unit, and send the data requests to the corresponding modules for processing according to the request type, and return the processing results to the front-end graphical unit.

[0010] Furthermore, the user interface unit includes:

[0011] Component library unit, used to classify and store various components in the rural energy revolution;

[0012] A modeling area unit is used for the user to perform modeling operations, and the modeling operations include: arranging, connecting, deleting or selecting the component elements;

[0013] The property unit is used for allowing the user to input parameter information of each component element and displaying the parameter information of each component element.

[0014] Further, the front-end event general scheduling unit includes an event trigger analyzer and a data communication trigger, wherein the event trigger analyzer is used to call the corresponding function stored in the digital twin core unit to respond to the user's operation when the function function stored in the digital twin core unit can independently respond to the user's operation;

[0015] The data communication trigger is used to send the operation information to the cloud system when the function function stored in the digital twin core unit cannot respond to the user's operation independently. The cloud system then responds to the user's operation together with the function function stored in the digital twin core unit.

[0016] Furthermore, the digital twin modeling module in the cloud system is also used to compare the calculated energy efficiency index with the energy efficiency index benchmark value and output the comparison result.

[0017] Furthermore, it also includes: a database unit, which includes: a basic information database subunit, used to store basic information of typical energy systems in the rural energy revolution, including model, type and rated power; a spatial database subunit, used to store user operation location information; an energy efficiency benchmark value database subunit, used to store energy efficiency index benchmark values.

[0018] Furthermore, the database unit also includes: a template database sub-unit, which is used to store the topological connection relationship between various component elements of the typical energy system in the rural energy revolution.

[0019] Furthermore, the topology management module in the cloud system also includes: a template reading unit, which is used to read the data in the template database subunit and transmit it to the front-end graphics unit.

[0020] Furthermore, the database unit also includes: a calculation database subunit, which is used to store calculation results of energy efficiency indicators.

[0021] Furthermore, the digital twin modeling module in the cloud system includes:

[0022] The component energy efficiency index calculation unit is used to calculate the energy efficiency related indexes of each component element constituting the energy system. The calculation formula is:

[0023]

[0024] Among them, η component Represents the energy efficiency of the component element, P out Represents the output power of the component element, P in Represents the input power of the component element;

[0025] The energy system energy efficiency index calculation unit is used to calculate the energy efficiency related indexes of the energy system composed of various components. The calculation formula is:

[0026]

[0027] Among them, η system represents the energy efficiency of the energy system, n is the number of components in the system, P out,i is the output power of the ith component, m is the number of components that need to input energy in the system, P in,j is the input power of the jth component.

[0028] Furthermore, the cloud system also includes:

[0029] The storage process unit is used to store all the data that need to be stored sent by the front-end graphical unit into the database unit, including but not limited to the energy efficiency index of the component element and the energy efficiency index of the energy system, and their comparison results with the benchmark values.

[0030] According to the above-mentioned embodiment of the present invention, at least the following beneficial effects are achieved: the rural energy revolution digital twin modeling system based on cloud-edge collaboration provided by the present invention can effectively improve the digital management level and energy efficiency of rural energy systems. Through the collaborative work of the user interface unit, the digital twin core unit and the front-end event general scheduling unit, users can conveniently perform digital twin modeling operations, and the system can quickly respond to various operation information of users, call corresponding function functions, and realize accurate feedback of user operations. In addition, the system can optimize the data processing process through the cloud-edge collaboration module, improve the data processing speed and accuracy, and make the digital twin modeling of rural energy revolution more efficient and practical. The database unit of the system can further enhance the management capability of energy system information, and can store and manage basic information of typical energy systems in rural energy revolution, user operation location information, energy efficiency index benchmark values ​​and other data. Through the introduction of template database subunits and calculation database subunits, the system can more flexibly process and analyze the topological connection relationship of energy systems and the calculation results of energy efficiency indicators. The realization of these functions can provide users with richer and deeper data analysis results, thereby providing strong data support for the decision-making of rural energy revolution. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0032] Figure 1 A structural schematic diagram of a rural energy revolution digital twin modeling system based on cloud-edge collaboration provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0033] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0034] Those skilled in the art know that the embodiments of the present invention can be implemented as a system, device, apparatus, method or computer program product. Therefore, the present invention can be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0035] It should be noted that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0036] Reference below Figure 1 , Figure 1 A schematic diagram of the structure of a rural energy revolution digital twin modeling system based on cloud-edge collaboration provided by an embodiment of the present invention. Figure 1 As shown, a rural energy revolution digital twin modeling system 100 based on cloud-edge collaboration includes:

[0037] A front-end graphical unit consisting of at least a user interface unit, a digital twin core unit and a front-end event general scheduling unit, wherein the user interface unit is used to interact with the user, receive parameters input by the user and provide the user with digital twin modeling;

[0038] The digital twin core unit is used to store a variety of functional functions related to digital twin modeling operations, and the various functional functions can support the user's digital twin modeling operations;

[0039] The front-end event general scheduling unit is used to receive various operation information of the user and call corresponding function to respond to the user's operation;

[0040] A cloud-based system consisting of at least a cloud-edge collaboration module, a monomer modeling module, a topology management module and a digital twin modeling module, wherein the cloud-edge collaboration module is used to receive data requests sent by the front-end graphical unit, and send the data requests to the corresponding modules for processing according to the request type, and return the processing results to the front-end graphical unit.

[0041] It should be noted that the collaborative work of the front-end graphical unit, the digital twin core unit, and the front-end event general scheduling unit provides users with an intuitive and feature-rich operating interface, enabling users to conveniently perform digital twin modeling. The design of this system allows users to input parameters through the interactive interface, while the system backend can process these inputs and perform corresponding modeling operations.

[0042] Specifically, the user interface unit includes multiple sub-units, such as the component library unit, the modeling area unit, and the attribute unit, which are responsible for storing component elements, providing modeling space, and inputting and displaying component parameters. The digital twin core unit stores a series of functional functions that can be called and executed according to the user's modeling needs. The front-end event scheduling unit is responsible for monitoring the user's interactive actions and triggering the corresponding functional functions or passing the operation information to the cloud system for processing.

[0043] Preferably, the user interface unit may further include a real-time rendering engine to provide a smoother and more intuitive modeling experience. The functional functions in the digital twin core unit may include but are not limited to geometric modeling, physical simulation, data analysis, etc. to support complex modeling tasks. The front-end event general scheduling unit may adopt an event-driven programming model to ensure rapid response to user operations. In addition, the cloud-edge collaboration module in the cloud system can be designed to have load balancing and failover capabilities to improve the stability and reliability of the system.

[0044] In some embodiments, the user interface unit includes:

[0045] Component library unit, used to classify and store various components in the rural energy revolution;

[0046] A modeling area unit is used for the user to perform modeling operations, and the modeling operations include: arranging, connecting, deleting or selecting the component elements;

[0047] The property unit is used for allowing the user to input parameter information of each component element and displaying the parameter information of each component element.

[0048] It should be noted that the component library unit can be designed as a database containing a variety of energy components, such as photovoltaic panels, wind turbines, and energy storage devices. These components can be stored in categories and have corresponding attribute labels, such as model, type, and rated power. The modeling area unit provides a visual workspace where users can drag, drop, arrange, and connect components. The attribute unit is a parameter configuration interface that allows users to enter and adjust parameters for the selected component, while displaying the real-time parameter information of the component.

[0049] Preferably, the component library unit may further include 3D models and animations of the components to provide a more intuitive preview effect. The modeling area unit may integrate advanced graphic editing tools, such as the functions of aligning, distributing and locking components, as well as undo and redo operation history. The property unit may be designed to support batch editing and import and export functions of parameters to meet complex modeling requirements. In addition, the user interface unit may also include a real-time feedback system to dynamically update the parameters and status of the components according to the user's operation to enhance the user interaction experience.

[0050] In some embodiments, the front-end event general scheduling unit includes an event trigger analyzer and a data communication trigger, wherein the event trigger analyzer is used to call the corresponding function stored in the digital twin core unit to respond to the user's operation when the function function stored in the digital twin core unit can independently respond to the user's operation;

[0051] The data communication trigger is used to send the operation information to the cloud system when the function function stored in the digital twin core unit cannot respond to the user's operation independently. The cloud system then responds to the user's operation together with the function function stored in the digital twin core unit.

[0052] It should be noted that the event trigger analyzer can be designed as an intelligent monitoring system that can identify the operations performed by the user on the user interface unit and determine whether these operations can be processed independently by the digital twin core unit. If so, it will directly call the corresponding function in the core unit to process these operations. The data communication trigger is responsible for sending the operation information to the cloud system when the core unit cannot process the operation independently, and working with the core unit to jointly complete the response to the user operation.

[0053] Preferably, the event trigger analyzer can adopt a rule-based algorithm or machine learning model to improve the recognition accuracy and response speed of user operations. The data communication trigger can be designed to support multiple communication protocols and data formats to adapt to different network environments and devices. In addition, the front-end event general scheduling unit can also include a priority system to prioritize user operations to ensure that key operations can be processed first. A user operation history function can also be implemented to allow users to trace back and re-execute previous modeling steps.

[0054] In some embodiments, the digital twin modeling module in the cloud system is also used to compare the calculated energy efficiency index with the energy efficiency index baseline value and output the comparison result.

[0055] It should be noted that the digital twin modeling module in the cloud system is not only responsible for modeling the energy system, but also undertakes the important task of evaluating and comparing energy efficiency. This module evaluates the performance of the energy system by comparing the calculated energy efficiency index with the preset benchmark value.

[0056] Specifically, the digital twin modeling module can be designed to include two main calculation units: the component meta-energy efficiency index calculation unit and the energy system energy efficiency index calculation unit. The component meta-energy efficiency index calculation unit calculates the energy efficiency of a single component based on the input and output power, while the energy system energy efficiency index calculation unit comprehensively considers the energy efficiency of all components in the system to obtain the energy efficiency index of the entire system. These calculation results are then compared with the energy efficiency benchmark values ​​stored in the database unit to evaluate whether the system meets the expected energy efficiency standards.

[0057] Preferably, the digital twin modeling module can further integrate an intelligent recommendation system. When the calculated energy efficiency index is lower than the benchmark value, the system can automatically recommend optimization solutions, such as adjusting component configuration or operating parameters. In addition, the module can also be designed to support the setting of custom benchmark values ​​to meet the needs of different users or different application scenarios. A real-time monitoring interface can also be implemented to display real-time data and historical trends of energy efficiency, so that users can intuitively understand system performance and make corresponding adjustments.

[0058] In some embodiments, it also includes: a database unit, which includes: a basic information database subunit, used to store basic information of typical energy systems in the rural energy revolution, including model, type and rated power; a spatial database subunit, used to store user operation location information; an energy efficiency benchmark value database subunit, used to store energy efficiency index benchmark values.

[0059] It should be noted that the database unit is designed to store and manage key data in the rural energy revolution, which is essential for the operation of the digital twin modeling system. The database unit consists of multiple sub-units, each of which is responsible for storing different types of information.

[0060] Specifically, the database unit includes a basic information database subunit, which is used to store detailed information about each component in the energy system, such as model, type, and rated power; a spatial database subunit, which is used to record the specific location information of user operations, which may include geographic coordinates, altitude, etc.; and an energy efficiency benchmark database subunit, which is used to save efficiency standards or ideal efficiency values ​​for different energy systems. These benchmark values ​​can be used to evaluate actual energy efficiency. Together, these subunits form a comprehensive data storage and management system that provides the necessary data support for digital twin modeling.

[0061] Preferably, the database unit can adopt a distributed database system to improve the reliability and access speed of data storage. The basic information database subunit can contain additional component information, such as manufacturer, production date and maintenance records. The spatial database subunit can be expanded to support the storage of three-dimensional spatial data to adapt to more complex geographic information system (GIS) applications. The energy efficiency benchmark value database subunit can be designed to allow users to update and maintain benchmark values ​​according to different time periods or different operating conditions. In addition, the database unit can integrate data encryption and access control mechanisms to ensure the security and privacy of the data.

[0062] In some embodiments, the database unit further includes: a template database subunit for storing topological connection relationships between typical energy system component elements in the rural energy revolution.

[0063] It should be noted that the expansion of the database unit adds a template database subunit, which is specifically used to store and manage the topological connection relationship between the component elements of a typical energy system in the rural energy revolution. In this way, the system can record and understand the interactions and connections between different components, providing accurate network structure information for digital twin modeling.

[0064] Specifically, the template database subunit may include multiple topology templates that define standard component connection methods for different types of energy systems. Each template may include a series of component element identifiers, connection port definitions, and connection order and rules. In addition, the template may also include layout information of the component elements, such as physical location, relative orientation, etc., to support more accurate modeling and analysis.

[0065] Preferably, the template database subunit can be designed to support the function of user-defined templates, allowing users to create or modify topology templates according to actual energy system conditions. The system can provide template editing tools to enable users to design component connections in a graphical manner. In addition, the template database subunit can integrate version control functions to track the change history of the template to ensure data consistency and traceability. Template import and export functions can also be implemented to facilitate sharing and migration of topology templates between different projects or different systems.

[0066] In some embodiments, the topology management module in the cloud system further includes: a template reading unit, which is used to read the data in the template database subunit and transmit it to the front-end graphics unit.

[0067] It should be noted that the topology management module in the cloud system is endowed with the function of a template reading unit, which is to effectively read and apply the data stored in the template database subunit. The introduction of the template reading unit strengthens the system's ability to manage and apply the topological connection relationship of energy system components.

[0068] Specifically, the template reading unit can be designed as a data interface, which can access the template database subunit to retrieve and extract the required topology template data. These data include not only the connection relationship between component elements, but also the properties and parameters of the connection, such as voltage level, current capacity, etc. The template reading unit passes these data to the front-end graphical unit for users to use in the modeling process.

[0069] Preferably, the template reading unit may have the function of data parsing and conversion, and convert the extracted template data into a format that can be recognized and processed by the user interface unit. In addition, in order to improve the efficiency of data retrieval, the template reading unit may implement a search mechanism based on keywords or classifications to quickly locate a specific topology template. A cache mechanism may also be designed to temporarily store template data that is frequently accessed by users, so as to reduce the number of database accesses and improve the system response speed. More specifically, the template reading unit may be designed to support real-time data updates, and when the data in the template database subunit changes, the latest data can be synchronized to the front-end graphical unit in a timely manner.

[0070] In some embodiments, the database unit further includes: a calculation database subunit, which is used to store calculation results of the energy efficiency index.

[0071] It should be noted that the database unit is further expanded to add a calculation database subunit, which is specially used to store the calculation results of energy efficiency indicators. This design enables the system to retain historical calculation data, which is convenient for trend analysis and efficiency evaluation.

[0072] Specifically, the calculation database subunit can be designed to store the calculation results of the energy efficiency index of each component element or the entire energy system, including but not limited to the output power, input power of the component element and the energy efficiency ratio at the system level. These data can be indexed by timestamp to facilitate historical data analysis and comparison. In addition, the calculation database subunit can also record the context information of the calculation results, such as calculation parameters, date and time, etc.

[0073] Preferably, the computational database subunit can be designed to support efficient data query and indexing mechanisms to meet the needs of rapid retrieval of large amounts of data. The system can provide a user interface that enables users to query and browse computational results based on specific parameters or time periods. In addition, the computational database subunit can integrate data backup and recovery functions to ensure data security and reliability.

[0074] More specifically, the computational database subunit can implement automated data maintenance strategies, such as regular data cleansing and optimization, to maintain database performance. Data compression technology can also be used to reduce storage space requirements. In addition, the system can be designed to support data visualization, presenting the calculation results to users in the form of charts or graphs, so that users can intuitively understand the changing trends of energy efficiency. A prediction model can also be implemented to predict future energy efficiency indicators based on historical data to provide decision support for users.

[0075] In some embodiments, the digital twin modeling module in the cloud system includes:

[0076] The component energy efficiency index calculation unit is used to calculate the energy efficiency related indexes of each component element constituting the energy system. The calculation formula is:

[0077]

[0078] Among them, η component Represents the energy efficiency of the component element, P out Represents the output power of the component element, P in Represents the input power of the component element;

[0079] The energy system energy efficiency index calculation unit is used to calculate the energy efficiency related indexes of the energy system composed of various components. The calculation formula is:

[0080]

[0081] Among them, η system represents the energy efficiency of the energy system, n is the number of components in the system, P out,i is the output power of the ith component, m is the number of components that need to input energy in the system, P in,j is the input power of the jth component.

[0082] It should be noted that the specific implementation of the digital twin modeling module in the cloud system involves detailed calculation methods for component elements and energy system energy efficiency indicators. These calculation methods provide a scientific basis for the system to quantitatively evaluate energy efficiency.

[0083] Specifically, the component element energy efficiency index calculation unit is calculated according to the formula

[0084]

[0085] To evaluate the energy efficiency of a single component, P out is the output power of the module, P in is the input power. The energy efficiency index calculation unit of the energy system is based on the formula

[0086]

[0087] to calculate the energy efficiency of the entire energy system, where n is the number of components in the system, P out,i is the output power of the ith component, m is the number of components that require energy input, P in,j is the input power of the jth component.

[0088] Preferably, the digital twin modeling module can realize automated data collection and calculation processes. The system can preset the data collection cycle and collect power data from various components in the energy system at regular intervals. The calculation unit can update the energy efficiency index in real time based on the collected data. In addition, the system can be designed to support input and output power calculations of multiple energy types to adapt to different types of energy systems.

[0089] More specifically, the digital twin modeling module can integrate a user configuration interface that allows users to customize relevant parameters of power calculation, such as selecting the calculation period, setting the accuracy of power measurement, etc. The system can also implement a data verification mechanism to ensure the accuracy of the collected power data. In addition, the module can be designed to support the export function of calculation results, so that users can use the calculation results of energy efficiency indicators for further analysis or reporting. A prediction function can also be implemented to predict future energy efficiency trends based on historical data to help users with long-term energy planning and optimization.

[0090] In some embodiments, the cloud system further includes:

[0091] The storage process unit is used to store all the data that need to be stored sent by the front-end graphical unit into the database unit, including but not limited to the energy efficiency index of the component element and the energy efficiency index of the energy system, and their comparison results with the benchmark values.

[0092] It should be noted that the storage process unit in the cloud system is the key component responsible for persistent storage. It ensures that all data sent by the front-end graphical unit can be safely and accurately stored in the database unit.

[0093] Specifically, the stored procedure unit can be designed to contain a set of predefined stored procedures that define how to insert, update, or delete data into database records. The stored procedures can include logic for data validation, formatting, and optimization to ensure data consistency and integrity. In addition, the stored procedure unit can interact with the various subunits of the database unit to achieve the storage of basic information, spatial information, energy efficiency indicators, and their comparison results.

[0094] Preferably, the stored procedure unit can use parameterized queries to improve the security of data storage and prevent security issues such as SQL injection. The stored procedure can be designed to support transaction processing to ensure the atomicity, consistency, isolation and persistence of data storage. In addition, the stored procedure unit can integrate performance monitoring tools to track and optimize the performance of data storage.

[0095] More specifically, the stored process unit can implement an automated data backup and recovery mechanism to cope with system failures or data loss. A user interface can be designed to allow users to manually trigger the data storage process, or to automatically execute the storage process based on specific trigger conditions. In addition, the stored process unit can support data version control and record historical changes to facilitate auditing and backtracking. A data encryption storage function can also be implemented to ensure the security of stored data and prevent unauthorized access.

[0096] The above-mentioned embodiments of the present invention have the following beneficial effects: The rural energy revolution digital twin modeling system based on cloud-edge collaboration provided by the present invention can realize a user-friendly interactive interface and efficient data processing capability through a highly integrated front-end graphical unit, a digital twin core unit and a front-end event general scheduling unit. The system can respond to the parameters input by the user in real time, call the corresponding function, and realize accurate digital twin modeling operations. In addition, the cloud-edge collaboration module in the cloud system can optimize the processing flow of data requests, improve the response speed and data processing capability of the system, and ensure the efficiency and accuracy of digital twin modeling, especially in rural environments with limited resources and unstable networks. In addition, the system can enhance the management capability of energy system information through the expansion of the database unit, and can not only store and manage the basic information of typical energy systems in the rural energy revolution, but also record the specific location information of user operations and the benchmark value of energy efficiency indicators. Through the introduction of the template database subunit and the calculation database subunit, the system can more flexibly process and analyze the topological connection relationship of the energy system and the calculation results of the energy efficiency index. The realization of these functions can provide users with richer and more in-depth data analysis results, thereby providing strong data support for decision-making in the rural energy revolution and promoting the intelligent and refined management of rural energy use.

[0097] Furthermore, the storage medium of the embodiment of the present application stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0098] The above descriptions are only some preferred embodiments of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present invention is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present invention to form a technical solution.

Claims

1. A rural energy revolution digital twin modeling system based on cloud-edge collaboration, characterized by: include: A front-end graphical unit consisting of at least a user interface unit, a digital twin core unit and a front-end event general scheduling unit, wherein the user interface unit is used to interact with the user, receive parameters input by the user and provide the user with digital twin modeling; The digital twin core unit is used to store a variety of functional functions related to digital twin modeling operations, and the various functional functions can support the user's digital twin modeling operations; The front-end event general scheduling unit is used to receive various operation information of the user and call corresponding function to respond to the user's operation; A cloud-based system consisting of at least a cloud-edge collaboration module, a monomer modeling module, a topology management module and a digital twin modeling module, wherein the cloud-edge collaboration module is used to receive data requests sent by the front-end graphical unit, and send the data requests to the corresponding modules for processing according to the request type, and return the processing results to the front-end graphical unit.

2. The system according to claim 1, characterized in that The user interface unit comprises: Component library unit, used to classify and store various components in the rural energy revolution; A modeling area unit is used for the user to perform modeling operations, and the modeling operations include: arranging, connecting, deleting or selecting the component elements; The property unit is used for allowing the user to input parameter information of each component element and displaying the parameter information of each component element.

3. The system according to claim 1 or 2, characterized in that: The front-end event general scheduling unit includes an event trigger analyzer and a data communication trigger, wherein the event trigger analyzer is used to call the corresponding function function stored in the digital twin core unit to respond to the user's operation when the function function stored in the digital twin core unit can independently respond to the user's operation; The data communication trigger is used to send the operation information to the cloud system when the function function stored in the digital twin core unit cannot respond to the user's operation independently. The cloud system then responds to the user's operation together with the function function stored in the digital twin core unit.

4. The system according to claim 1, characterized in that The digital twin modeling module in the cloud system is also used to compare the calculated energy efficiency index with the energy efficiency index benchmark value and output the comparison result.

5. The system according to claim 4, characterized in that Also includes: A database unit, the database unit comprising: a basic information database subunit, for storing basic information of typical energy systems in the rural energy revolution, including model, type and rated power; The spatial database subunit is used to store user operation location information; the energy efficiency benchmark value database subunit is used to store energy efficiency index benchmark values.

6. The system according to claim 5, characterized in that The database unit also includes: a template database sub-unit, which is used to store the topological connection relationship between various component elements of a typical energy system in the rural energy revolution.

7. The system according to claim 6, characterized in that The topology management module in the cloud system also includes: a template reading unit, which is used to read the data in the template database subunit and transmit it to the front-end graphics unit.

8. The system according to claim 5, characterized in that The database unit also includes: a calculation database subunit, which is used to store the calculation results of the energy efficiency index.

9. The system according to claim 8, characterized in that The digital twin modeling module in the cloud system includes: The component energy efficiency index calculation unit is used to calculate the energy efficiency related indexes of each component element constituting the energy system. The calculation formula is: Among them, η component Represents the energy efficiency of the component element, P out Represents the output power of the component element, P in Represents the input power of the component element; The energy system energy efficiency index calculation unit is used to calculate the energy efficiency related indexes of the energy system composed of various components. The calculation formula is: Among them, η system represents the energy efficiency of the energy system, n is the number of components in the system, P out,i is the output power of the ith component, m is the number of components that need to input energy in the system, P in,j is the input power of the jth component.

10. The system according to claim 1, characterized in that The cloud system also includes: The storage process unit is used to store all the data that need to be stored sent by the front-end graphical unit into the database unit, including but not limited to the energy efficiency index of the component element and the energy efficiency index of the energy system, and their comparison results with the benchmark values.

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