Point cloud data-based distribution network non-power-cut operation decision-making system and method

Abstract

The invention belongs to the technical field of distribution networks, and particularly relates to a point cloud data-based distribution network non-power-cut operation decision-making system and a point cloud data-based distribution network non-power-cut operation decision-making method. The system aims to solve the problem that traditional operation decision depends on experience judgment and field investigation, and intelligent decision of distribution network non-power-cut operation is achieved by integrating a point cloud data acquisition module, a key parameter calculation module, a three-dimensional scene reconstruction module, an operation scheme acquisition module, a three-dimensional deduction module and the like. The system can obtain a point cloud data image of a power distribution operation site, calculate equipment parameters, construct a three-dimensional scene model, and deduce an operation scheme in the three-dimensional scene model so as to determine an optimal non-power-cut operation decision scheme. In addition, the system further comprises a calculation module for parameters such as towers, wires, roads and obstacles and functions such as input, storage and deduction analysis of operation schemes, and finally, deduction scores and analysis data are displayed through a display module, so that scientific basis and decision support are provided for power-off-free operation of the distribution network.

Description

Technical Field

[0001] The present invention belongs to the technical field of distribution networks, and specifically relates to a distribution network non-stop operation decision system and method based on point cloud data. Background Art

[0002] The distribution network refers to the power grid that receives electric energy from the transmission network or regional power plants and distributes it locally or step by step according to the voltage to various users through distribution facilities. It is composed of overhead lines, cables, towers, distribution transformers, disconnectors, reactive power compensators and some ancillary facilities, and plays an important role in distributing electric energy in the power grid. In the power industry, non-stop operation of the distribution network is an important means to ensure the stable operation of the power grid and the reliability of power supply. However, traditional operation decisions often rely on experience judgment and on-site investigation, which is not only time-consuming and labor-intensive, but also difficult to fully and accurately assess the risks and effects of operations. Summary of the invention

[0003] The purpose of the present invention is to provide a distribution network non-stop operation decision system and method based on point cloud data to solve the problem that traditional operation decisions often rely on experience judgment and on-site investigation.

[0004] To achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a distribution network non-stop operation decision system based on point cloud data, comprising: Point cloud data acquisition module, used to acquire point cloud data images of the power distribution operation site; The key parameter calculation module is used to calculate the equipment parameters at the power distribution operation site based on the point cloud data image of the power distribution operation site; A 3D scene reconstruction module is used to construct a 3D scene model based on the point cloud data image of the power distribution operation site and the equipment parameters of the power distribution operation site; An operation plan acquisition module is used to obtain a non-stop operation plan for the distribution network; The three-dimensional deduction module is used to deduce the distribution network non-stop power supply operation plan in the constructed three-dimensional scenario model to determine the non-stop power supply operation decision plan.

[0005] As an optional solution of the present invention, the key parameter calculation module includes: A tower parameter calculation module is used to calculate tower parameters based on the point cloud data image collected by the point cloud data acquisition module; A wire parameter calculation module, used to calculate the wire parameters according to the point cloud data image collected by the point cloud data acquisition module; A road parameter calculation module, used to calculate road parameters according to the point cloud data image collected by the point cloud data acquisition module; The obstacle parameter calculation module is used to calculate the obstacle parameters according to the point cloud data image collected by the point cloud data acquisition module.

[0006] As an optional solution of the present invention, the three-dimensional scene reconstruction module includes: A data acquisition module is used to acquire tower parameters, conductor parameters, road parameters, obstacle parameters, and point cloud data images collected by the point cloud data acquisition module; A data storage module, used for storing the data acquired by the data acquisition module; The model building module is used to build a three-dimensional scene model according to the data stored in the data storage module.

[0007] As an optional solution of the present invention, the operation plan acquisition module includes: Input module, used to input the non-stop operation plan of the distribution network; The storage module is used to store the entered distribution network non-stop operation plan.

[0008] As an optional solution of the present invention, the three-dimensional deduction module includes: The substitution module is used to substitute the data stored in the storage module into the three-dimensional scene model for deduction; A recording module is used to record the deduction process; An analysis module, used for analyzing the deduction process recorded by the recording module; The scoring module is used to score the deduction process based on the data analyzed by the analysis module.

[0009] As an optional solution of the present invention, a display module is also included to display the scores scored by the scoring module and the data analyzed by the analysis module.

[0010] As an optional solution of the present invention, the point cloud data acquisition module acquires point cloud data of the work site based on a three-dimensional scanning device.

[0011] In a second aspect, the present invention provides a method for decision-making on non-stop power supply operations in a distribution network based on point cloud data, comprising: Obtain point cloud data images of the power distribution operation site; Calculate the equipment parameters at the power distribution operation site based on the point cloud data image of the power distribution operation site; Construct a 3D scene model based on the point cloud data image of the power distribution operation site and the equipment parameters of the power distribution operation site; Obtain the non-stop operation plan for the distribution network; The distribution network non-stop operation plan is deduced in the constructed three-dimensional scenario model to determine the non-stop operation decision plan.

[0012] According to a third aspect of the present invention, there is provided an electronic device, comprising a processor and a memory, wherein the processor is configured to execute a computer program stored in the memory to implement the above-mentioned method for making decisions on non-stop power supply operations in a distribution network.

[0013] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by a processor, the distribution network non-stop operation decision method as described above is implemented.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: The distribution network non-stop operation decision system of the present invention can accurately and quickly obtain the point cloud data image of the distribution operation site through the point cloud data acquisition module and the three-dimensional scene reconstruction module, and construct a detailed three-dimensional scene model based on it. It greatly improves the efficiency of on-site investigation before the operation, reduces the investment of manpower and material resources, and also reduces the operation risk caused by inaccurate on-site investigation. The key parameter calculation module can accurately calculate the equipment parameters of the distribution operation site, such as the parameters of poles, towers, wires, roads and obstacles, based on the point cloud data image, providing a solid foundation for subsequent deduction and analysis, and ensuring the accuracy and reliability of operation decisions. The three-dimensional deduction module can deduce the distribution network non-stop operation plan in the constructed three-dimensional scene model, so as to determine the best operation decision plan, improve the accuracy of operation decisions, discover and solve potential safety hazards in the deduction process, and further ensure the safety and reliability of operations.

[0015] In addition, the system also includes an operation plan acquisition module and a display module, which can easily input, store and display the operation plan and its deduction score and analysis data. This makes the operation decision-making process more transparent and traceable, and provides strong support for subsequent operation execution and effect evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings constituting a part of the present application are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 This is a structural block diagram of a distribution network non-stop operation decision system based on point cloud data according to an embodiment of the present invention; Figure 2 This is a flow chart of a method for decision-making on non-stop power supply operations in a distribution network based on point cloud data according to an embodiment of the present invention; Figure 3 The present invention is a structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0017] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0018] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention.

[0019] Example 1 With the development of 3D scanning technology and computer simulation technology, 3D deduction methods based on point cloud data are gradually applied to the decision-making of distribution network non-stop operation, providing a new way for the formulation and optimization of operation plans. Point cloud data is obtained by scanning the site with 3D scanning equipment, which contains rich spatial information and geometric features. In the non-stop operation of the distribution network, point cloud data can be used to construct a 3D scene model of the distribution operation site, thereby realizing the virtualization and visualization of the operation environment. Through the 3D scene model, the equipment layout, spatial relationship and potential risk points of the operation site can be intuitively understood, providing strong support for the formulation of the operation plan. However, relying solely on point cloud data and 3D scene models is not enough to formulate the optimal operation plan. The calculation and extraction of key parameters are the basis for formulating the operation plan. In the non-stop operation of the distribution network, the key parameters that need to be calculated include the height, position, and inclination angle of the tower, the length, diameter, and direction of the wire, the width, length, and slope of the road, and the size, position, and type of obstacles. The calculation of these parameters requires high-precision algorithms and professional knowledge to ensure the accuracy and reliability of the calculation results.

[0020] When formulating an operation plan, it is also necessary to consider the combined impact of multiple factors. For example, the skill level of the operator, the availability of the required tools and equipment, the time limit for the operation, etc. There are often complex relationships and constraints between these factors, which need to be optimized and coordinated through scientific decision-making methods and tools. The three-dimensional deduction module is such a tool. It can substitute the operation plan into the three-dimensional scene model for deduction, and evaluate the feasibility and effect of the operation plan by simulating the actual operation process. During the deduction process, relevant data and information need to be recorded in real time for subsequent analysis and scoring. These data include changes in equipment status, execution of operation steps, etc. Through the analysis and scoring of the deduction process, problems and deficiencies in the operation plan can be found, and corresponding improvement measures can be proposed. At the same time, personnel, equipment and time can be reasonably arranged according to the deduction results to improve resource utilization efficiency.

[0021] The present invention provides a decision-making system for distribution network non-stop operation based on point cloud data. The system combines 3D scanning technology, computer simulation technology and scientific decision-making methods, can realize virtualization and visualization of the operation environment, and provide strong support for the formulation and optimization of operation plans. Through this system, the operation risks and effects can be quickly and accurately evaluated, the operation quality and safety can be improved, and contributions can be made to the sustainable development of the power industry.

[0022] See also Figure 1 , a distribution network non-stop operation decision system based on point cloud data, including: Point cloud data acquisition module, used to acquire point cloud data images of the power distribution operation site; The key parameter calculation module is used to calculate the equipment parameters at the power distribution operation site based on the point cloud data image of the power distribution operation site; A 3D scene reconstruction module is used to construct a 3D scene model based on the point cloud data image of the power distribution operation site and the equipment parameters of the power distribution operation site; An operation plan acquisition module is used to obtain a non-stop operation plan for the distribution network; The three-dimensional deduction module is used to deduce the distribution network non-stop power supply operation plan in the constructed three-dimensional scenario model to determine the non-stop power supply operation decision plan.

[0023] In one embodiment, the point cloud data is obtained by scanning the site with a three-dimensional scanning device, and the three-dimensional scanning device may be a laser radar, etc. The three-dimensional scanning device scans the work site and sends it to the point cloud data acquisition module.

[0024] In one embodiment, the key parameter calculation module calculates various key parameters of the power distribution operation site by processing the point cloud data image acquired by the point cloud data acquisition module.

[0025] Specifically, the key parameter calculation module includes: A tower parameter calculation module is used to calculate tower parameters based on the point cloud data image collected by the point cloud data acquisition module; A wire parameter calculation module, used to calculate the wire parameters according to the point cloud data image collected by the point cloud data acquisition module; A road parameter calculation module, used to calculate road parameters according to the point cloud data image collected by the point cloud data acquisition module; The obstacle parameter calculation module is used to calculate the obstacle parameters according to the point cloud data image collected by the point cloud data acquisition module.

[0026] More specifically, the tower parameter calculation module is specifically used to: identify the outline and key feature points of the tower in the point cloud data, such as the tower top, tower bottom, tower body, etc. According to the identified key feature points, calculate the tower's height, diameter, tilt angle and other parameters.

[0027] More specifically, the conductor parameter calculation module is specifically used for: Identify the outline and key feature points of the wire in the point cloud data, such as the starting point, end point, and bend of the wire. Segment the identified wire part from the entire point cloud data for subsequent parameter calculation.

[0028] Calculate the length of the wire: Calculate the length of the wire based on the segmented wire point cloud data. You can calculate the distance between adjacent points in the wire point cloud data and add up these distances to get the total length of the wire.

[0029] Calculate wire diameter: In the wire point cloud data, select multiple sections for diameter measurement. The wire diameter can be obtained by calculating the average of the maximum distance and the minimum distance of the points in the section.

[0030] Calculate the direction and inclination angle of the wire: Analyze the spatial distribution of the wire point cloud data, and calculate the direction of the wire (i.e. the extension direction of the wire) and the inclination angle (i.e. the angle between the wire and the horizontal plane).

[0031] More specifically, the road parameter calculation module is specifically used for: Identify the road area in the point cloud data, including key features such as road boundaries and lane lines. Segment the identified road area from the entire point cloud data for subsequent parameter calculation.

[0032] Calculate road width: In the segmented road point cloud data, select multiple cross sections for width measurement. By calculating the distance between the boundary points on both sides of the road on each cross section, the average width of the road can be obtained.

[0033] Calculate road length: Calculate the total length of the road based on the spatial distribution of the road point cloud data. The total length of the road can be obtained by calculating the distances between adjacent points in the road point cloud data and adding up these distances.

[0034] Calculate road slope and curvature: Analyze the spatial distribution of road point cloud data and calculate the road slope (i.e. the angle between the road and the horizontal plane) and curvature (i.e. the degree of road curvature). This can be achieved by comparing the height difference and horizontal distance of different locations in the road point cloud data.

[0035] More specifically, the obstacle parameter calculation module is specifically used for: Identify the outline and key feature points of obstacles in the point cloud data, such as the shape, size, position, etc. of the obstacles. Segment the identified obstacle parts from the entire point cloud data for subsequent parameter calculation.

[0036] Calculate obstacle size: Based on the segmented obstacle point cloud data, use the algorithm to calculate the obstacle's length, width, height and other size parameters. This can be achieved by calculating the distance between key feature points in the obstacle point cloud data.

[0037] Calculate obstacle position: Determine the specific position of obstacles in three-dimensional space. This can be achieved by calculating the centroid or center point of the obstacle point cloud data.

[0038] Calculate the distance between obstacles and key areas: According to the specific conditions of the power distribution operation site, determine the key areas (such as operation areas, safety areas, etc.) and calculate the distance between obstacles and key areas.

[0039] Identify obstacle types: Identify the type of obstacle (such as trees, buildings, vehicles, etc.) based on its shape, material and other features, so that targeted processing can be carried out later.

[0040] In one embodiment, the 3D scene reconstruction module includes: A data acquisition module is used to acquire tower parameters, conductor parameters, road parameters, obstacle parameters, and point cloud data images collected by the point cloud data acquisition module; A data storage module, used for storing the data acquired by the data acquisition module; The model building module is used to build a three-dimensional scene model according to the data stored in the data storage module.

[0041] Specifically, the data acquisition module is used to receive data from the key parameter calculation module and the point cloud data acquisition module, including the height, position, inclination angle of the tower, the length, diameter, direction of the wire, the width, length, slope of the road, the size, position, type of obstacles, and the point cloud data image from the point cloud data acquisition module.

[0042] Specifically, the data storage module is designed with a database for storing point cloud data and its related parameters. The database contains multiple tables, which are used to store tower parameters, conductor parameters, road parameters, obstacle parameters and point cloud data images. The parameter data collected from the data acquisition module and the collected point cloud data images are stored in the corresponding database tables according to the predetermined format and rules.

[0043] Specifically, the model building module reads the stored tower parameters, conductor parameters, road parameters, obstacle parameters and point cloud data images from the database, and integrates these data to form a complete data set for subsequent 3D scene model building. Use 3D modeling software (such as AutoCAD, 3ds Max, SketchUp, etc.) to build a 3D scene model based on the integrated data set. During the modeling process, the actual shape, size and position relationship of the towers, conductors, roads and obstacles are considered to ensure the accuracy and authenticity of the model. The established 3D scene model is optimized, including adjusting the details of the model, optimizing the geometric structure of the model, and improving the rendering efficiency of the model.

[0044] In one embodiment, the operation plan acquisition module includes: Input module, used to input the non-stop operation plan of the distribution network; The storage module is used to store the entered distribution network non-stop operation plan.

[0045] Specifically, the input module is used to receive and record relevant information of the distribution network non-stop operation plan, including the operation location, operation time, operation personnel, required tools and equipment, operation steps, etc.

[0046] To be more specific, the function implementation of the input module includes: creating an input interface that contains all necessary fields and options for entering detailed information of the distribution network non-stop operation plan. According to the content and requirements of the distribution network non-stop operation plan, define all necessary input fields, such as operation time, operation location, operation type, operation personnel, operation tools, operation steps, etc. Write code to implement the data entry function, allowing users to enter relevant information of the distribution network non-stop operation plan through the input interface. When the user enters data, real-time verification and feedback are performed to ensure the accuracy and compliance of the data.

[0047] Specifically, the storage module is used to store the distribution network non-stop operation plan information received and processed by the input module into a database, and the operating personnel can retrieve and view this information at any time when needed.

[0048] Specifically, the functions of the storage module include: designing a database table structure based on the content and requirements of the distribution network non-stop operation plan to store relevant information of the operation plan. Writing code to implement the data storage function and save the input distribution network non-stop operation plan data to the database. Writing code to provide a data query interface, allowing users to query the distribution network non-stop operation plan data stored in the database according to their needs. The query interface provides multiple query methods, such as query by time range, query by operation location, etc., to meet the different needs of users.

[0049] In one embodiment, the three-dimensional deduction module includes: The substitution module is used to substitute the data stored in the storage module into the three-dimensional scene model for deduction; A recording module is used to record the deduction process; An analysis module, used for analyzing the deduction process recorded by the recording module; A scoring module is used to score the deduction process based on the data analyzed by the analysis module; The display module is used to display the scores given by the scoring module and the data analyzed by the analysis module.

[0050] Specifically, the substitution module is used to substitute the data stored in the storage module into the constructed three-dimensional scene model; it involves data reading, parsing and mapping.

[0051] Data reading: Read the data to be substituted from the storage module.

[0052] Data parsing: Parse the read data and extract the required information.

[0053] Data mapping: Map the parsed information to the corresponding elements in the 3D scene model, such as mapping the location information of the device to the device model in the model.

[0054] Specifically, the recording module is used to record the deduction process for subsequent analysis and scoring; it involves the collection, organization and storage of data.

[0055] Data collection: During the simulation process, relevant data is collected in real time, such as changes in equipment status, execution status of operation steps, etc.

[0056] Data collation: Sort the collected data, remove redundant information, and retain key data.

[0057] Data storage: Store the organized data in a specified location for subsequent use.

[0058] Specifically, the analysis module is used to analyze the deduction process recorded by the recording module, extract key information, and evaluate the effect of the deduction; it involves data mining, statistics and analysis.

[0059] Data mining: extract useful information from recorded data, such as equipment failure rate, operating efficiency, etc.

[0060] Data statistics: Statistics are performed on the mined information and relevant indicators are calculated, such as mean value, standard deviation, etc.

[0061] Data analysis: Based on the statistical results, analyze the problems and room for improvement in the deduction process.

[0062] For example, using the mean formula To calculate the average value of a certain indicator; The standard deviation formula can be used To evaluate the degree of dispersion of the data.

[0063] Specifically, the scoring module is used to score the deduction process based on the data analyzed by the analysis module; it involves the formulation of scoring criteria, the selection of scoring methods and the calculation of scoring results.

[0064] Scoring criteria formulation: Based on the objectives and requirements of the simulation, formulate scoring criteria and clarify the weights and scoring criteria of each indicator.

[0065] Selection of scoring method: Select an appropriate scoring method, such as weighted average method, fuzzy comprehensive evaluation method, etc.

[0066] Calculation of scoring results: Calculate the total score of the deduction process based on the scoring criteria and scoring method.

[0067] For example, you can use the weighted average formula To calculate the total score, w i is the weight of each indicator, x i It is the score of each indicator.

[0068] Specifically, the display module is used to display the scores given by the scoring module and the data analyzed by the analysis module; it involves data visualization processing and user interface design.

[0069] Data visualization: Visualize the data from the analysis module and the scoring module, such as drawing charts, generating reports, etc.

[0070] User Interface Design: Design the user interface so that users can easily view and analyze data.

[0071] For example, in data visualization, graph drawing algorithms are used to generate clear charts and reports.

[0072] The decision-making system provided by the above embodiment, through the three-dimensional deduction module, allows users to quickly compare and evaluate multiple operation plans in a virtual environment, so as to quickly find the optimal plan. By simulating the actual operation process, potential safety hazards can be discovered and avoided to ensure the safety of operators. According to the deduction results, personnel, equipment and time can be reasonably arranged to improve resource utilization efficiency. Through the three-dimensional scene model and deduction process, the accuracy and feasibility of the operation plan can be ensured, thereby improving the quality of the operation.

[0073] Example 2 like Figure 2As shown, based on the same inventive concept as the above embodiment, the present invention also provides a distribution network non-stop operation decision method, the specific steps are as follows: S1. Obtaining point cloud data images of the power distribution operation site; S2. Calculate the equipment parameters of the power distribution operation site based on the point cloud data image of the power distribution operation site; S3, constructing a three-dimensional scene model based on the point cloud data image of the power distribution operation site and the equipment parameters of the power distribution operation site; S4. Obtain a non-stop operation plan for the distribution network; S5. Deducing the non-stop operation plan of the distribution network in the constructed three-dimensional scenario model to determine the decision-making plan for non-stop operation.

[0074] In an optional embodiment, a method for making decisions on non-stop power supply operations in a distribution network comprises the following specific steps: S100, acquiring a point cloud data image of a power distribution operation site through a point cloud data acquisition module; S200, calculating the tower parameters by the tower parameter calculation module according to the point cloud data image collected by the point cloud data acquisition module, calculating the wire parameters by the wire parameter calculation module according to the point cloud data image collected by the point cloud data acquisition module, calculating the road parameters by the road parameter calculation module according to the point cloud data image collected by the point cloud data acquisition module, and calculating the obstacle parameters by the obstacle parameter calculation module according to the point cloud data image collected by the point cloud data acquisition module; S300, acquiring tower parameters, conductor parameters, road parameters, obstacle parameters and point cloud data images collected by the point cloud data acquisition module through the data acquisition module, storing the point cloud data images acquired by the data acquisition module through the data storage module, and after storage, establishing a three-dimensional scene model according to the data stored in the data storage module through the model establishment module; S400, inputting a distribution network non-stop power operation plan through an input module, and storing the input distribution network non-stop power operation plan through a storage module; S500. Substitute the data stored in the storage module into the three-dimensional scene model for deduction through the substitution module, record the deduction process through the recording module, analyze the deduction process recorded by the recording module through the analysis module, score the deduction process according to the data analyzed by the analysis module through the scoring module, and in this process, display the score given by the scoring module and the data analyzed by the analysis module through the display module.

[0075] Example 3 like Figure 3 As shown, the present invention also provides an electronic device 100 for implementing a method for making decisions on non-stop power distribution network operations; The electronic device 100 includes a memory 101 , at least one processor 102 , a computer program 103 stored in the memory 101 and executable on the at least one processor 102 , and at least one communication bus 104 .

[0076] The memory 101 can be used to store a computer program 103. The processor 102 implements the steps of a distribution network non-stop operation decision method in Example 2 by running or executing the computer program stored in the memory 101 and calling the data stored in the memory 101.

[0077] The memory 101 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data (such as audio data) created according to the use of the electronic device 100, etc. In addition, the memory 101 may include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0078] At least one processor 102 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 102 may be a microprocessor or any conventional processor, etc. The processor 102 is the control center of the electronic device 100, and uses various interfaces and lines to connect various parts of the entire electronic device 100.

[0079] The memory 101 in the electronic device 100 stores a plurality of instructions to implement a method for making decisions on power distribution network non-stop operation, and the processor 102 can execute the plurality of instructions to implement: Obtain point cloud data images of the power distribution operation site; Calculate the equipment parameters at the power distribution operation site based on the point cloud data image of the power distribution operation site; Construct a 3D scene model based on the point cloud data image of the power distribution operation site and the equipment parameters of the power distribution operation site; Obtain the non-stop operation plan for the distribution network; The distribution network non-stop operation plan is deduced in the constructed three-dimensional scenario model to determine the non-stop operation decision plan.

[0080] Example 4 If the module / unit integrated in the electronic device 100 is implemented in the form of 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 present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. Computer-readable media may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory and read-only memory (ROM, Read-Only Memory).

[0081] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0082] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0083] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0084] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0085] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A distribution network non-stop operation decision system based on point cloud data, characterized in that: include: Point cloud data acquisition module, used to acquire point cloud data images of the power distribution operation site; A key parameter calculation module, used to calculate the equipment parameters at the power distribution operation site according to the point cloud data image; A three-dimensional scene reconstruction module, used to construct a three-dimensional scene model according to the point cloud data image and the device parameters; An operation plan acquisition module is used to obtain a non-stop operation plan for the distribution network; The three-dimensional deduction module is used to deduce the distribution network non-stop power supply operation plan in the constructed three-dimensional scenario model to determine the non-stop power supply operation decision plan.

2. The distribution network non-stop operation decision system according to claim 1 is characterized in that: The key parameter calculation module specifically includes: A tower parameter calculation module is used to calculate tower parameters based on point cloud data images; A wire parameter calculation module is used to calculate the wire parameters according to the point cloud data image; A road parameter calculation module, used to calculate road parameters based on point cloud data images; The obstacle parameter calculation module is used to calculate the obstacle parameters according to the point cloud data image.

3. The distribution network non-stop operation decision system according to claim 1 is characterized in that: The three-dimensional scene reconstruction module specifically includes: A data acquisition module is used to acquire tower parameters, conductor parameters, road parameters, obstacle parameters, and point cloud data images collected by the point cloud data acquisition module; A data storage module, used for storing the data acquired by the data acquisition module; The model building module is used to build a three-dimensional scene model according to the data stored in the data storage module.

4. The distribution network non-stop operation decision system according to claim 1, characterized in that: The operation plan acquisition module specifically includes: Input module, used to input the non-stop operation plan of the distribution network; The storage module is used to store the entered distribution network non-stop operation plan.

5. The distribution network non-stop operation decision system according to claim 1 is characterized in that: The three-dimensional deduction module specifically includes: The substitution module is used to substitute the data stored in the storage module into the three-dimensional scene model for deduction; A recording module is used to record the deduction process; An analysis module, used for analyzing the deduction process recorded by the recording module; The scoring module is used to score the deduction process based on the data analyzed by the analysis module.

6. The distribution network non-stop operation decision system according to claim 5, characterized in that: It also includes a display module for displaying the scores given by the scoring module and the data analyzed by the analysis module.

7. The distribution network non-stop operation decision system according to claim 1, characterized in that: The point cloud data acquisition module acquires point cloud data of the work site based on a three-dimensional scanning device.

8. A distribution network non-stop operation decision-making method based on point cloud data, characterized in that: include: Obtain point cloud data images of the power distribution operation site; Calculating equipment parameters at the power distribution operation site according to the point cloud data image; Constructing a three-dimensional scene model according to the point cloud data image and the device parameters; Obtain the non-stop operation plan for the distribution network; The distribution network non-stop operation plan is deduced in the constructed three-dimensional scenario model to determine the non-stop operation decision plan.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the processor is used to execute a computer program stored in the memory to implement the distribution network non-stop operation decision method as claimed in claim 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores at least one instruction, and when the at least one instruction is executed by the processor, the distribution network non-stop operation decision method according to claim 8 is implemented.

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