Digital power grid processing method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a digital power grid processing method and device, electronic equipment and a storage medium. The method comprises the following steps: performing grid division on a power distribution network, and determining a plurality of power grid community grids; for each power grid community grid, constructing a digital twinborn model of the power grid community grid according to the real-time power data and the three-dimensional live-action data of the power grid community grid; displaying the digital twinborn model through a digital power grid middle platform; under the condition that the reported work order of the power grid community grid is obtained, analysis is carried out based on the digital twinborn model and the reported work order, and a target demand and a target solution are obtained; and displaying the target demand and the target solution of the grid of the power grid community through the digital power grid middle station. The method is used for achieving the effect of improving the response efficiency of the digital power grid.

Description

Technical Field

[0001] This application relates to the field of power grid technology, and in particular to a digital power grid processing method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the development of power systems, digital grids have become an important direction for improving the quality and efficiency of power supply services.

[0003] In related technologies, the operation of power equipment, grid maintenance, and power supply services in a digital power grid are independent of each other. To meet users' electricity needs, it is necessary to coordinate multiple departments to resolve them, resulting in low response efficiency of power supply services. Summary of the Invention

[0004] This application provides a digital power grid processing method, apparatus, electronic device, and storage medium to improve the response efficiency of the digital power grid.

[0005] In a first aspect, embodiments of this application provide a digital power grid processing method, comprising:

[0006] The distribution network is divided into grids, and multiple power grid community grids are determined.

[0007] For each power grid community grid, a digital twin model of the power grid community grid is constructed based on the real-time power data and 3D real-scene data of the power grid community grid;

[0008] The digital twin model is displayed through the digital power grid platform;

[0009] Once the reported work orders from the power grid community grid are obtained, the target requirements and target solutions are derived through analysis based on the digital twin model and the reported work orders.

[0010] The digital power grid platform displays the target needs and solutions for the power grid community grid.

[0011] In one possible implementation, a digital twin model of the power grid community grid is constructed based on real-time power data and 3D reality data, including:

[0012] Obtain real-time power data of power equipment in the power grid community grid;

[0013] Based on lidar inspection equipment, obtain three-dimensional real-scene data of the power distribution network in the power grid community grid;

[0014] A digital twin model of the power grid community grid is constructed based on real-time power data and 3D real-scene data.

[0015] In one possible implementation, acquiring real-time power data of electrical equipment in the power grid community grid includes:

[0016] By using asset data from the digital power grid platform, the power equipment in the power grid community grid is identified; the power equipment includes medium-voltage side smart power equipment and low-voltage side smart power equipment.

[0017] Obtain real-time power data from medium-voltage side intelligent power equipment;

[0018] Real-time power data on the low-voltage side is obtained from intelligent power equipment on the low-voltage side.

[0019] In one possible implementation, analysis is performed based on the digital twin model and reported work orders to obtain target requirements and target solutions, including:

[0020] Extract the data to be processed from the reported work orders; the data to be processed includes text data and / or image data.

[0021] By analyzing the data to be processed using a large model, the target requirements can be obtained;

[0022] By processing the digital twin model and target requirements through a large model, the target solution is obtained.

[0023] In one possible implementation, the target requirements include at least one of the following: fault resolution requirements, power supply guarantee requirements, and application requirements;

[0024] By processing the digital twin model and target requirements through a large-scale model, the target solution is obtained, including:

[0025] When the target requirement is a fault resolution requirement, the digital twin model and the fault resolution requirement are processed through a large model to obtain the target fault solution; the target fault solution includes: faulty equipment, fault cause, and fault elimination plan;

[0026] When the target demand is power supply guarantee demand, the digital twin model and power supply guarantee demand are processed through a large model to obtain the target power supply guarantee scheme; the target power supply guarantee scheme includes: the power supply guarantee area, and the power supply strategy of the power supply guarantee area.

[0027] In one possible implementation, the distribution network is gridded to determine multiple grid community grids, including:

[0028] Acquire static attribute data and dynamic operation data of power equipment in the power distribution network;

[0029] Based on the static attribute data and dynamic operation data of the power equipment, determine the corresponding equipment nodes of the power equipment;

[0030] Determine the connection edges between equipment nodes based on the line connections between power equipment;

[0031] Construct a power distribution network topology based on device nodes and connection edges;

[0032] The distribution network topology is divided into grids using a graph neural network, resulting in multiple power grid community grids.

[0033] Secondly, embodiments of this application provide a digital power grid processing apparatus, comprising:

[0034] The grid partitioning module is used to partition the distribution network into grids and determine multiple power grid community grids;

[0035] The model building module is used to construct a digital twin model of each power grid community grid based on the real-time power data and 3D real-scene data of the power grid community grid.

[0036] The first display module is used to display the digital twin model through the digital power grid platform;

[0037] The work order processing module is used to analyze the reported work orders from the power grid community grid based on the digital twin model and the reported work orders to obtain the target requirements and target solutions.

[0038] The second display module is used to display the target needs and target solutions of the power grid community grid through the digital power grid platform.

[0039] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0040] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0041] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0042] The digital power grid processing method, apparatus, electronic device, and storage medium provided in this application embodiment are as follows: The digital power grid processing method of this application embodiment divides the distribution network into grids, determines multiple power grid community grids, provides a foundation for subsequent regional management of the digital power grid based on the power grid community grids, constructs and displays digital twin models for the power grid community grids based on real-time power data and 3D real-scene data, provides a visual and interactive digital twin model, realizes the transparency of distribution network operation, distribution network assets, and operation; after obtaining the reported work orders from the power grid community grids, it automatically analyzes and obtains the target requirements and target solutions, displays the target requirements and target solutions through the digital power grid middle platform, realizes operation and distribution coordination, improves the efficiency of government-enterprise linkage, and improves the fault resolution and demand response efficiency of the digital power grid. Attached Figure Description

[0043] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0044] Figure 1 Flowchart of the digital power grid processing method provided in this application Figure 1 ;

[0045] Figure 2 Flowchart of the digital power grid processing method provided in this application Figure 2 ;

[0046] Figure 3 Flowchart of the digital power grid processing method provided in this application Figure 3 ;

[0047] Figure 4 A schematic diagram of the structure of the digital power grid processing device provided in this application;

[0048] Figure 5 A schematic diagram of the structure of the electronic device provided in this application.

[0049] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0050] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0051] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0052] Figure 1 Flowchart of the digital power grid processing method provided in this application Figure 1 The processing methods of digital power grids can be applied to electronic devices, which can be terminals; such as... Figure 1 As shown, the processing methods for digital power grids include:

[0053] S101. Divide the distribution network into grids and determine multiple power grid community grids.

[0054] Among them, the power grid community grid is a part of the distribution network; the power grid community grid can be divided according to the electricity consumption in the distribution network, or it can correspond to the community grid divided according to administrative division data and community division data.

[0055] Optionally, the administrative division data of the geographical area corresponding to the distribution network and the administrative division data of the geographical area are obtained. The distribution network is divided into grids according to the community grids in the administrative division data to obtain multiple power grid community grids.

[0056] In some embodiments, the distribution network is divided into grids to determine multiple power grid community grids, including: acquiring static attribute data and dynamic operation data of power equipment in the distribution network; determining the equipment nodes corresponding to the power equipment based on the static attribute data and dynamic operation data of the power equipment; determining the connection edges between equipment nodes based on the line connections between power equipment; constructing a distribution network topology map based on the equipment nodes and connection edges; and dividing the distribution network topology map into grids using a graph neural network to obtain multiple power grid community grids.

[0057] Static attribute data includes, but is not limited to: type of power equipment, physical parameters, geographical location, and substation area; dynamic operation data includes power operation data, such as voltage, power factor, and power load.

[0058] Specifically, based on the static attribute data and dynamic operation data of each power device in the distribution network, the power devices are mapped to device nodes. The node data of the device nodes includes the static attribute data and dynamic operation data of the power devices. Based on the power grid topology, the line connection relationship between power devices is determined. Based on the line connection between power devices, the connection edge between device nodes is determined. The static attributes of the line (such as name, electrical distance, etc.) are the edge attributes of the connection edge.

[0059] A power distribution network topology is constructed based on the equipment nodes, the node data of the equipment nodes, the static attributes of the lines, and the edge attributes of the connecting edges.

[0060] The adjacency matrix is ​​determined based on the power distribution network topology. For example, if there are N device nodes, the dimension of the adjacency matrix is... If there is a connecting edge between device node i and device node j, then in the adjacency matrix... The value is 1 if the value is not equal to 1, and zero otherwise. The node characteristic matrix is ​​determined based on the distribution network topology diagram; for example, the node characteristic matrix is... Each row represents the node data of a device node, and the node data includes data in F dimensions.

[0061] The adjacency matrix and feature matrix are input into the graph neural network to obtain the node embedding matrix. The node embedding matrix includes the fingerprint features of each device node. The fingerprint features are learned from the relevant node data and are an abstract representation containing complex structural and relational information. The node embedding matrix is ​​clustered to obtain multiple clusters. That is, based on the similarity between fingerprint features, device nodes with closer electrical connections and coordinated load modes are grouped into one cluster. Multiple power grid community grids are determined based on multiple clusters.

[0062] In the above embodiments, a distribution network topology map is constructed based on the static attribute data, dynamic operation data, and topological relationships between power equipment. The distribution network topology map is then divided using a graph neural network to obtain multiple power grid community grids. This ensures that the division of the power grid community grids matches the actual electricity consumption situation, thereby improving the accuracy of the power grid community grid division.

[0063] S102. For each power grid community grid, construct a digital twin model of the power grid community grid based on the real-time power data and 3D real-scene data of the power grid community grid.

[0064] Among them, real-time power data includes dynamic operation data of each power device in the power grid community grid; 3D real-scene data is 3D point cloud data of the power grid community network.

[0065] Digital twin models refer to models constructed in digital space using data from physical entities or systems, which are fully mapped, interact in real time, and can be intelligently controlled.

[0066] Specifically, for each power grid community grid, the power equipment in the power grid community grid has an automatic data reporting function to obtain real-time power data automatically reported by the power equipment; the three-dimensional real scene data can be the three-dimensional real scene data obtained in each inspection cycle, that is, at each preset time interval, the inspection cycle is entered, and in the inspection cycle, the three-dimensional real scene data of the power grid community grid is obtained by drones; a three-dimensional real scene model is constructed based on the three-dimensional real scene data, and a digital twin model of the power grid community grid is constructed based on the three-dimensional real scene model and the factual power data of the power grid community grid.

[0067] S103. Display the digital twin model through the digital power grid platform.

[0068] Specifically, the data power grid platform has a real-view function page, which displays a digital twin model.

[0069] The digital twin model can be interactively displayed by zooming in or out, and providing detailed information about power equipment.

[0070] Digital twin models of multiple power grid community grids can be combined to form a digital twin model of the entire distribution network. A digital twin model of one power grid community grid can be used to jump to a digital twin model of another power grid community grid.

[0071] By displaying a digital twin model on the data power grid platform, a visual and interactive three-dimensional model is provided, realizing transparency in distribution network operation, distribution network assets, and operations.

[0072] S104. After obtaining the reported work orders from the power grid community grid, analyze the digital twin model and the reported work orders to obtain the target requirements and target solutions.

[0073] Among them, the reported work order can be submitted by users, staff, organizational structures and other electricity users; in practical applications, electricity users can submit reported work orders through the service application (or service website) in cases of abnormal electricity use or power supply needs.

[0074] Among them, the target demand is the electricity demand obtained by analyzing the content of the reported work orders.

[0075] Specifically, the reported work orders from the power grid community grid are obtained, and the reported work orders and digital twin models are analyzed through a large model to determine the target requirements and target solutions for the reported work orders.

[0076] In some embodiments, such as Figure 2 As shown, the analysis based on the digital twin model and the reported work order yields the target requirements and target solutions, including: S201, extracting the data to be processed from the reported work order; the data to be processed includes text data and / or image data; S202, analyzing the data to be processed through the large model to obtain the target requirements; S203, processing the digital twin model and target requirements through the large model to obtain the target solutions.

[0077] The reported work orders include power outage work orders, power supply guarantee work orders, and installation application work orders.

[0078] Specifically, text data and / or image data are extracted from the reported work orders, and the text data and / or image data are processed through a large model to obtain the target requirements; the target requirements include the requirement type and requirement information.

[0079] For example, the demand type is a fault type, and the demand information is fault information (e.g., power outage area, power outage time); for example, the demand type is a power supply guarantee type, and the demand information is specific information about the power supply guarantee (e.g., the area, time, and specific activities of the power supply guarantee); for example, the demand type is an application type, and the demand information includes the application equipment and the application address.

[0080] By processing the digital twin model and target requirements through a large model, the target solution is obtained.

[0081] In the above embodiments, electricity users can submit work orders themselves. The digital power grid platform analyzes the digital twin model and the submitted work orders to obtain the target solution, effectively supporting the response to users' personalized needs, realizing the coordination of operation and maintenance, and improving the efficiency of government-enterprise linkage. By processing the digital twin model and the submitted work orders through a large model, the reliability of the target solution is improved.

[0082] In some embodiments, the target requirement includes at least one of: fault resolution requirement and power supply guarantee requirement; processing the digital twin model and the target requirement through a large model to obtain a target solution includes: when the target requirement is a fault resolution requirement, processing the digital twin model and the fault resolution requirement through a large model to obtain a target fault solution; the target fault solution includes: faulty equipment, fault cause, and fault elimination plan; when the target requirement is a power supply guarantee requirement, processing the digital twin model and the power supply guarantee requirement through a large model to obtain a target power supply guarantee plan; the target power supply guarantee plan includes: power supply guarantee area, and power supply strategy for the power supply guarantee area.

[0083] Specifically, when the target requirement is a fault resolution requirement, fault information is obtained from the fault resolution requirement, and power grid topology data and power equipment data related to the fault information are obtained from the digital twin model; the fault information, the topology data and power equipment data related to the fault information are processed by the large model to obtain the fault solution; optionally, the target requirement and the target fault solution are displayed on the digital twin model through the digital power grid platform, so that operation and maintenance personnel can intuitively determine the current power grid fault and the corresponding solution through the digital power grid platform, thereby improving the response efficiency of power grid faults.

[0084] When the target demand is power supply guarantee demand, the power supply guarantee area and power supply guarantee time are obtained from the power supply guarantee demand; the power grid topology data and power equipment data corresponding to the power supply guarantee area are obtained from the digital twin model; the power grid topology data, power equipment data and power supply guarantee time corresponding to the power supply guarantee area are processed by the large model to obtain the target power supply guarantee scheme.

[0085] The target power supply guarantee scheme includes: a power supply guarantee area and a power supply strategy for the power supply guarantee area; wherein, the power supply guarantee area may include at least one power grid community grid, or a part of a power grid community grid.

[0086] For example, power supply strategies include: multiple power supply guarantees (such as main grid power supply, emergency generator vehicles, uninterruptible power supplies, etc.), and staffing according to the areas to be guaranteed power supply.

[0087] In the above embodiments, the large model is used to handle fault resolution needs and power supply guarantee needs, thereby achieving operational coordination, improving the efficiency of government-enterprise collaboration, and enhancing the reliability of the target solution.

[0088] S105. Display the target needs and target solutions of the power grid community grid through the digital power grid platform.

[0089] Optionally, the target requirement is a fault resolution requirement. The data power grid platform has a user requirement page, which displays the fault resolution requirement and the corresponding target solution.

[0090] Optionally, the target requirement is power supply guarantee requirement. The data power grid platform has a government-enterprise linkage page, which displays the power supply guarantee requirement and the corresponding target solution.

[0091] The data grid highlights target needs and solutions, achieving transparency in distribution network operation, distribution network assets, and operations.

[0092] The digital power grid processing method provided in this application divides the distribution network into grids, determining multiple power grid community grids. This provides a foundation for subsequent regional management of the digital power grid based on the power grid community grids. For each power grid community grid, a digital twin model is constructed and displayed based on real-time power data and 3D real-scene data, providing a visual and interactive digital twin model. This achieves transparency in distribution network operation, distribution network assets, and operations. Upon receiving work orders reported by the power grid community grids, the method automatically analyzes and obtains target requirements and solutions. These target requirements and solutions are then displayed through the digital power grid platform, achieving operational and distribution coordination, improving government-enterprise collaboration efficiency, and enhancing the efficiency of fault resolution and demand response in the digital power grid.

[0093] In some embodiments, such as Figure 3 As shown, a digital twin model of the power grid community grid is constructed based on real-time power data and 3D real-scene data of the power grid community grid, including: S301, obtaining real-time power data of the power grid community grid based on the power equipment of the power grid community grid; S302, obtaining 3D real-scene data of the power distribution network of the power grid community grid based on the lidar inspection equipment; S303, constructing a digital twin model of the power grid community grid based on real-time power data and 3D real-scene data of the power grid community grid.

[0094] Among them, real-time power data refers to the dynamic operation data mentioned above.

[0095] Specifically, all power equipment in the power grid community grid is intelligent power equipment with automatic reporting function, which obtains real-time power data automatically reported by the power equipment in the power grid community grid; when entering the inspection cycle, drones equipped with LiDAR are used to inspect the power grid community network, and during the inspection process, LiDAR scanning is used to obtain the three-dimensional point cloud data (three-dimensional real scene data) of the power grid community grid; the three-dimensional real scene data reported by the drone is also obtained.

[0096] A 3D reality model is constructed based on 3D reality data, and a digital twin model of the power grid community grid is constructed based on the 3D reality model and the factual power data of the power grid community grid.

[0097] In the above embodiments, the digital twin model of the power grid community grid integrates electrical topology, equipment ledger and real-time operation data, supports visualization simulation and decision support for distribution network operation, maintenance and emergency scenarios. Through the digital twin model, the invisible full perception of the distribution network is realized (the operation status of power equipment can be known without seeing the on-site power equipment), providing comprehensive power grid data, thereby improving decision-making capabilities and response efficiency.

[0098] In some embodiments, obtaining real-time power data of power equipment in a power grid community grid includes: identifying power equipment in the power grid community grid through asset data from a digital power grid platform; the power equipment includes medium-voltage side smart power equipment and low-voltage side smart power equipment; obtaining real-time power data of the medium-voltage side based on the medium-voltage side smart power equipment; and obtaining real-time power data of the low-voltage side based on the low-voltage side smart power equipment.

[0099] Among them, the digital power grid platform is a unified platform that aggregates data from all stages of planning, engineering, and operation and maintenance, and supports cross-departmental data sharing and collaborative analysis; asset data includes the full lifecycle data of power equipment and lines in the distribution network.

[0100] Among them, the intelligent power equipment on the medium-voltage side includes, but is not limited to: intelligent distribution switches, distribution terminal units (DTUs), and feeder terminal units (FTUs); the intelligent power equipment on the low-voltage side includes, but is not limited to: intelligent sensing terminals in transformer areas, smart meters, and leakage protection monitoring modules.

[0101] Specifically, intelligent distribution switches, distribution terminal units, and feeder terminal units are configured on the medium-voltage distribution network side; and intelligent sensing terminals, smart meters, and leakage protection monitoring modules are configured on the low-voltage distribution network side.

[0102] By using asset data from the digital power grid platform, the medium-voltage and low-voltage smart power equipment in the power grid community grid are identified. Real-time power data of the medium-voltage smart power equipment is obtained, and real-time power data of the low-voltage smart power equipment is determined.

[0103] It should be noted that intelligent distribution switches are used to automatically detect and quickly trip when a short circuit or ground fault occurs in the distribution network, isolating the faulty section; distribution terminal units and distribution terminal units are used to accurately detect and report fault current data, and are key equipment for fault location and isolation; intelligent sensing terminals for transformer areas are used to centrally collect data from the transformer area's main meter, data from each branch circuit, and data from downstream smart meters, realizing comprehensive perception of the "source-grid-load-storage" status within the transformer area; smart meters are used to measure the electricity consumed by users, monitor voltage, current, power outage / restoration events, etc.; and leakage protection monitoring modules are used to monitor leakage current and provide real-time alarms.

[0104] In the above embodiments, real-time power data includes real-time power data from medium-voltage side intelligent power equipment and real-time power data from low-voltage side intelligent power equipment. This data is used to construct a digital twin model of the power grid community grid, realizing intelligent medium-voltage distribution, transparent low-voltage distribution, and real-world distribution network. A fully perceptual model of the medium- and low-voltage distribution network is constructed, integrating IoT sensing terminals, intelligent power distribution equipment, and a 3D geographic information system to establish an "invisible, fully perceptual" intelligent 3D visual system. This provides comprehensive power grid data, thereby improving decision-making capabilities and response efficiency.

[0105] Optionally, the digital power grid platform aggregates information from all stages of planning, engineering, and operation and maintenance, enabling collaborative management and control of project progress, quality, safety, and cost; it formulates standardized technical specifications and acceptance standards for the digital construction of distribution networks, clarifies the principles for smart terminal deployment, communication access methods, data acquisition frequencies, and system interface protocols; and it develops a set of supporting management tools, including distribution network project dashboards, resource scheduling platforms, and performance evaluation models, to support management in dynamically monitoring and optimizing the entire process of demonstration zone construction.

[0106] Through the digital power grid platform, a comprehensive operation and maintenance management mechanism and a grid-based professional collaborative internal system have been established to proactively respond to the service demands of the government and users. Management systems and assessment mechanisms have been established and improved, business guidelines have been developed, and business processes have been optimized. Utilizing the internet, online electricity services are supported through methods such as reporting work orders via the power grid community grid, achieving zero-distance service, zero on-site visits, and zero proof required for electricity application. Furthermore, supporting power grid construction can be carried out in advance, enabling zero-investment applications for eligible users. Through operation and maintenance collaboration and government-enterprise linkage, zero-wait-for-electricity service has been achieved, improving the efficiency of fault resolution and demand response in the digital power grid.

[0107] In specific examples, a power grid brand exhibition hall that combines the functions of a business hall and an exhibition hall can be built in the demonstration area; digital business processing and cultural display services can be provided to enhance brand influence with the help of cultural and tourism resources; and the public's awareness of China Southern Power Grid's service culture can be improved through the display window, thus helping the development of the regional cultural and tourism industry.

[0108] Based on the practical experience of the demonstration zone, a replicable and scalable digital power grid domain management standard system was developed, including management specifications, technical guidelines, business process diagrams, job descriptions, and performance evaluation indicators. A dynamic optimization mechanism was established to continuously improve management processes and service models, supporting the promotion and application of this method in other urban areas or historical districts.

[0109] The digital power grid processing method provided in this application divides the distribution network into grids, determining multiple power grid community grids. This provides a foundation for subsequent regional management of the digital power grid based on the power grid community grids. For each power grid community grid, a digital twin model is constructed and displayed based on real-time power data and 3D real-scene data, providing a visual and interactive digital twin model. This achieves transparency in distribution network operation, distribution network assets, and operations. Upon receiving work orders reported by the power grid community grids, the method automatically analyzes and obtains target requirements and solutions. These target requirements and solutions are then displayed through the digital power grid platform, achieving operational and distribution coordination, improving government-enterprise collaboration efficiency, and enhancing the efficiency of fault resolution and demand response in the digital power grid.

[0110] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0111] Figure 4 A schematic diagram of the structure of the digital power grid processing device provided in this application is shown below. Figure 4 As shown, the digital power grid processing device 40 provided in this embodiment includes:

[0112] The grid division module 401 is used to divide the distribution network into grids and determine multiple power grid community grids.

[0113] Model building module 402 is used to build a digital twin model of each power grid community grid based on the real-time power data and 3D real-scene data of the power grid community grid.

[0114] The first display module 403 is used to display the digital twin model through the digital power grid platform;

[0115] The work order processing module 404 is used to analyze the reported work orders from the power grid community grid based on the digital twin model and the reported work orders to obtain the target requirements and target solutions.

[0116] The second display module 405 is used to display the target needs and target solutions of the power grid community grid through the digital power grid platform.

[0117] In some embodiments, the model building module is used to acquire real-time power data of power equipment in the power grid community grid; acquire three-dimensional real-scene data of the power distribution network of the power grid community grid based on the lidar inspection equipment; and construct a digital twin model of the power grid community grid based on the real-time power data and the three-dimensional real-scene data.

[0118] In some embodiments, the model building module is used to determine the power equipment of the power grid community grid through asset data of the digital power grid platform; the power equipment includes medium-voltage side smart power equipment and low-voltage side smart power equipment; real-time power data of the medium-voltage side is obtained based on the medium-voltage side smart power equipment; real-time power data of the low-voltage side is obtained based on the low-voltage side smart power equipment.

[0119] In some embodiments, the work order processing module is used to extract data to be processed based on the reported work order; the data to be processed includes text data and / or image data; the data to be processed is analyzed through a large model to obtain the target requirements; the digital twin model and the target requirements are processed through the large model to obtain the target solution.

[0120] In some embodiments, the work order processing module is used to process the target requirement, which includes at least one of a fault resolution requirement and a power supply guarantee requirement, and to process the digital twin model and the target requirement through a large model to obtain a target solution. This includes: when the target requirement is a fault resolution requirement, processing the digital twin model and the fault resolution requirement through a large model to obtain a target fault solution; the target fault solution includes: the faulty device, the cause of the fault, and the fault elimination plan; when the target requirement is a power supply guarantee requirement, processing the digital twin model and the power supply guarantee requirement through a large model to obtain a target power supply guarantee plan; the target power supply guarantee plan includes: the power supply guarantee area, and the power supply strategy for the power supply guarantee area.

[0121] In some embodiments, the grid partitioning module is used to: acquire static attribute data and dynamic operation data of power equipment in the distribution network; determine the equipment nodes corresponding to the power equipment based on the static attribute data and dynamic operation data of the power equipment; determine the connection edges between equipment nodes based on the line connections between power equipment; construct a distribution network topology map based on the equipment nodes and connection edges; and partition the distribution network topology map into grids using a graph neural network to obtain multiple power grid community grids.

[0122] The digital power grid processing device provided in this embodiment can execute the digital power grid processing method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0123] Figure 5 A schematic diagram of the structure of the electronic device provided in this application. Figure 5As shown, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, memory 502, and communication component 503 are connected via a bus.

[0124] In a specific implementation, at least one processor 501 executes computer execution instructions stored in memory 502, causing at least one processor 501 to perform the above-described method.

[0125] The specific implementation process of processor 501 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0126] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0127] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0128] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0129] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0130] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0131] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0132] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0133] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0134] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0135] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0136] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0137] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0138] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A processing method for a digital power grid, characterized in that, include: The distribution network is divided into grids, and multiple power grid community grids are determined. For each power grid community grid, a digital twin model of the power grid community grid is constructed based on the real-time power data and 3D real-scene data of the power grid community grid; The digital twin model is displayed through the digital power grid platform; Upon receiving the reported work orders from the power grid community grid, the target requirements and target solutions are obtained through analysis based on the digital twin model and the reported work orders. The digital power grid platform displays the target needs and target solutions for the power grid community grid.

2. The method according to claim 1, characterized in that, The process of constructing a digital twin model of the power grid community grid based on real-time power data and 3D real-scene data includes: Obtain real-time power data of power equipment in the power grid community grid; Based on the lidar inspection equipment, obtain the three-dimensional real-scene data of the power distribution network of the power grid community grid; Based on the real-time power data and 3D real-scene data, a digital twin model of the power grid community grid is constructed.

3. The method according to claim 2, characterized in that, The acquisition of real-time power data of power equipment in the power grid community grid includes: The power equipment in the power grid community grid is determined using the asset data from the digital power grid platform; the power equipment includes medium-voltage side smart power equipment and low-voltage side smart power equipment. The medium-voltage side intelligent power equipment is used to obtain real-time power data on the medium-voltage side. The low-voltage side intelligent power equipment acquires real-time power data on the low-voltage side.

4. The method according to claim 1, characterized in that, The analysis based on the digital twin model and the reported work order yields the target requirements and target solutions, including: Data to be processed is extracted from the reported work order; the data to be processed includes text data and / or image data. The target requirements are obtained by analyzing the data to be processed using a large model. The target solution is obtained by processing the digital twin model and the target requirements through a large model.

5. The method according to claim 4, characterized in that, The target requirements include at least one of the following: fault resolution requirements and power supply assurance requirements; The process of processing the digital twin model and the target requirements through a large model to obtain the target solution includes: When the target requirement is the fault resolution requirement, the digital twin model and the fault resolution requirement are processed through a large model to obtain the target fault solution; the target fault solution includes: faulty equipment, fault cause, and fault elimination plan; When the target demand is the power supply guarantee demand, the digital twin model and the power supply guarantee demand are processed through a large model to obtain the target power supply guarantee scheme; the target power supply guarantee scheme includes: the power supply guarantee area, and the power supply strategy of the power supply guarantee area.

6. The method according to any one of claims 1 to 5, characterized in that, The grid division of the distribution network, which determines multiple power grid community grids, includes: Acquire static attribute data and dynamic operation data of power equipment in the power distribution network; Based on the static attribute data and dynamic operation data of the power equipment, the corresponding equipment node is determined; Based on the line connections between the power equipment, determine the connection edges between the equipment nodes; Based on the device nodes and the connection edges, construct a power distribution network topology diagram; The power distribution network topology is divided into grids using a graph neural network to obtain multiple power grid community grids.

7. A processing device for a digital power grid, characterized in that, The device includes: The grid partitioning module is used to partition the distribution network into grids and determine multiple power grid community grids; The model building module is used to construct a digital twin model of each power grid community grid based on the real-time power data and 3D real-scene data of the power grid community grid. The first display module is used to display the digital twin model through the digital power grid platform; The work order processing module is used to analyze the reported work orders from the power grid community grid based on the digital twin model and the reported work orders to obtain target requirements and target solutions. The second display module is used to display the target needs and target solutions of the power grid community grid through the digital power grid platform.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, Includes computer execution instructions, which, when executed by a processor, implement the method as described in any one of claims 1 to 6.

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