Distribution network non-power-cut operation digital decision and scheme generation method and system based on live-action three-dimensional model

Abstract

The invention provides a distribution network non-power-cut operation digital decision and scheme generation method and system based on a live-action three-dimensional model. The method comprises the following steps: firstly, constructing a three-dimensional digital twinborn scene; receiving user job task information, positioning to a position corresponding to the scene, and calling a job method knowledge base to screen a preliminary candidate job method; and then simulating candidate method implementation in the scene, screening out qualified candidate methods through dynamic safety distance verification and feasibility analysis, generating a recommendation scheme sequence through quantitative evaluation comparison and selection, generating a preliminary job implementation scheme report according to template filling information, and finally receiving user auditing and modifying confirmation information and storing a final scheme. According to the method, the three-dimensional space relation of the line corridor is accurately reproduced by means of the three-dimensional digital twinning scene, quantitative data support is provided for operation method selection through multi-link simulation, verification and evaluation, information blind areas and misjudgment risks are eliminated, decision subjectivity is reduced, and rationality and safety of an operation scheme are guaranteed.

Description

A Method and System for Digital Decision-Making and Solution Generation in Distribution Network Live-Line Operations Based on Real-Scene 3D Models Technical Field

[0001] This invention belongs to the field of power distribution network live-line work technology, specifically relating to a digital decision-making and scheme generation method and system for power distribution network live-line work based on a real-scene 3D model. Background Technology

[0002] In the power system sector, live-line work on distribution networks is crucial for ensuring power supply reliability. With the continuous expansion of the power grid and the sustained growth of electricity demand, how to conduct live-line work on distribution networks efficiently and safely has become a critical issue that urgently needs to be addressed.

[0003] Traditional live-line work on power distribution networks relies primarily on two-dimensional drawings, tabular data, and the on-site memory of the workers. When faced with complex line corridor environments, this method struggles to comprehensively and accurately represent the spatial relationship between the lines and their surroundings. Furthermore, the selection of different work methods often heavily depends on the experience and judgment of seasoned workers.

[0004] Traditional operations cannot intuitively, comprehensively, and accurately reproduce the complex three-dimensional spatial relationships of railway corridors. The operational information is abstract, resulting in information blind spots and the risk of misjudgment. Furthermore, the applicability of different operational methods lacks quantitative data support and comparative analysis, leading to a high degree of subjectivity in the decision-making process and making it easy for unreasonable operational plans or potential safety hazards to occur. Summary of the Invention

[0005] In view of this, the present invention provides a method and system for digital decision-making and scheme generation for power distribution network uninterrupted operation based on a real-scene 3D model, aiming to solve the above-mentioned problems existing in the existing traditional operation methods.

[0006] To achieve the above objectives, the technical solution provided by the present invention is as follows:

[0007] In a first aspect, the present invention provides a method for digital decision-making and scheme generation for power distribution network uninterrupted operation based on a real-scene 3D model, comprising the following steps:

[0008] Acquire multi-source spatial data and equipment service attribute data of distribution network lines, construct a three-dimensional digital twin scene based on the multi-source spatial data, and associate and match the equipment service attribute data with spatial objects in the three-dimensional digital twin scene;

[0009] Receive the task information input by the user and locate the corresponding position in the 3D digital twin scene;

[0010] Retrieve the preset task method knowledge base and filter out several preliminary candidate task methods that match the current task.

[0011] The implementation process of each preliminary candidate operation method is simulated in a three-dimensional digital twin scenario, and dynamic safety distance verification and feasibility analysis are performed to select candidate operation methods that meet the requirements.

[0012] The candidate operation methods that meet the requirements are quantitatively evaluated and compared to generate a recommended solution sequence;

[0013] According to the preset report template data format, fill in the information of the recommended scheme sequence to generate a preliminary work implementation plan report;

[0014] Receive user feedback on the preliminary work implementation plan report, including review, modification, and confirmation, and save the final plan to complete the digital decision-making and plan generation for power distribution network uninterrupted operation.

[0015] Furthermore, the multi-source spatial data includes image data collected by UAV oblique photography, spatial point cloud data collected by laser point cloud scanning, and digital image data; the equipment business attribute data includes equipment specification parameter data, commissioning date data, and wire connection point coordinate data.

[0016] Furthermore, the task information includes the task route identifier, tower number, task type, and target phase; and it is located to the corresponding position in the 3D digital twin scene, including:

[0017] Extract the operation route identifier, tower number, operation type, and target phase from the operation task information as positioning features;

[0018] The positioning features are compared and matched with the spatial location identifiers of each spatial object in the 3D digital twin scene;

[0019] Based on the matched spatial objects, the corresponding tower and work area are located.

[0020] Furthermore, the work method knowledge base stores the applicable voltage levels, applicable working condition descriptions, required tools and equipment, and standard working hours for various live-line work methods in distribution networks; it then filters out several preliminary candidate work methods that match the current work task, including:

[0021] Based on the work line identifier, tower number, work type and target phase in the work task information, fuzzy matching is performed with the applicable voltage level and applicable working condition description in the work method knowledge base to select work methods whose adaptability meets the preset threshold as preliminary candidate work methods.

[0022] Extract the required tools and standard working hours for each preliminary candidate operation method.

[0023] Furthermore, dynamic safety distance verification and feasibility analysis are conducted, including:

[0024] Extract the motion trajectory coordinates of personnel and equipment during the implementation of each preliminary candidate operation method, combine them with the spatial coordinates of charged and grounded bodies in the three-dimensional digital twin scene, and use the preset distance calculation rules to calculate the minimum distance data between each point on the motion trajectory and the charged and grounded bodies;

[0025] Retrieve the safety distance threshold data and meteorological correction coefficient data for the corresponding voltage level, correct the minimum distance data, and conduct a comprehensive analysis in conjunction with the operational feasibility requirements. If the corrected minimum distance data is not less than the safety distance threshold and meets the feasibility requirements, the corresponding candidate operation method is selected; otherwise, the corresponding preliminary candidate operation method is eliminated.

[0026] Furthermore, the candidate operation methods that meet the requirements are quantitatively evaluated and compared to generate a recommended solution sequence, including:

[0027] Extract several evaluation index data corresponding to each candidate operation method that meets the requirements;

[0028] Retrieve the preset weight data of each evaluation indicator, standardize the data of each evaluation indicator, and then sum them up by weight to obtain the comprehensive evaluation score data of each candidate operation method.

[0029] Based on the comprehensive evaluation scores, the recommended solutions are generated by sorting them from high to low.

[0030] Furthermore, following the pre-set report template data format, the information of the recommended scheme sequence is filled in to generate a preliminary work implementation plan report, including:

[0031] Extract process data, required tool configuration data, safety control data, risk point data, and simulation process screenshot data for each scheme in the recommended scheme sequence;

[0032] Based on the bookmarks and content format requirements in the pre-set report template data, the various types of data extracted from the recommended scheme sequence are matched to the corresponding positions to generate a preliminary work implementation plan report.

[0033] Secondly, the present invention provides a digital decision-making and scheme generation system for uninterrupted power supply operations in distribution networks based on a real-world 3D model, comprising:

[0034] The 3D digital twin scene construction unit is used to acquire multi-source spatial data and equipment service attribute data of distribution network lines, construct a 3D digital twin scene based on the multi-source spatial data, and associate and match the equipment service attribute data with the spatial objects in the 3D digital twin scene.

[0035] The task receiving unit is used to receive task information input by the user and locate the corresponding position in the 3D digital twin scene;

[0036] The preliminary candidate method screening unit is used to retrieve a preset task method knowledge base and screen out several preliminary candidate task methods that match the current task.

[0037] The candidate method simulation implementation unit is used to simulate the implementation process of each preliminary candidate operation method in a three-dimensional digital twin scene, and to perform dynamic safety distance verification and feasibility analysis to screen out the candidate operation methods that meet the requirements.

[0038] The recommended solution sequence generation unit is used to quantitatively evaluate and compare candidate job methods that meet the requirements, and generate a recommended solution sequence.

[0039] The preliminary plan report generation unit is used to fill in the information of the recommended plan sequence according to the preset report template data format and generate a preliminary work implementation plan report;

[0040] The final solution generation unit is used to receive user feedback on the preliminary work implementation plan report, including review, modification, and confirmation information, and to save the final solution, thus completing the digital decision-making and solution generation for power distribution network live-line work.

[0041] Thirdly, the present invention provides a computer device, the device including a processor and a memory:

[0042] The memory is used to store computer programs and send the instructions of the computer programs to the processor;

[0043] The processor executes instructions from the computer program, such as the first aspect, a digital decision-making and scheme generation method for uninterrupted power distribution network operations based on a real-scene 3D model.

[0044] Fourthly, the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements a digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene three-dimensional model, as described in the first aspect.

[0045] In summary, this invention provides a method and system for digital decision-making and scheme generation for live-line work in distribution networks based on a real-world 3D model. The method includes the following steps: acquiring multi-source spatial data of distribution network lines and equipment service attribute data; constructing a 3D digital twin scene based on the multi-source spatial data; associating and matching the equipment service attribute data with spatial objects in the 3D digital twin scene; receiving user-inputted work task information and locating the corresponding position in the 3D digital twin scene; retrieving a preset work method knowledge base and selecting several preliminary candidate work methods that meet the current work task; simulating the implementation process of each preliminary candidate work method in the 3D digital twin scene, performing dynamic safety distance verification and feasibility analysis, and selecting candidate work methods that meet the requirements; quantitatively evaluating and comparing the candidate work methods that meet the requirements to generate a recommended scheme sequence; filling in the information of the recommended scheme sequence according to a preset report template data format to generate a preliminary work implementation plan report; receiving user review, modification, and confirmation information for the preliminary work implementation plan report, and saving the final scheme to complete the digital decision-making and scheme generation for live-line work in distribution networks. This invention constructs a three-dimensional digital twin scene, which can intuitively, comprehensively and accurately reproduce the three-dimensional spatial relationship of the railway corridor. Then, by performing three-dimensional simulation, dynamic safety distance verification and quantitative evaluation and comparison of candidate operation methods, it can provide quantitative data support for the selection of operation methods, effectively eliminate information blind spots and the risk of misjudgment, reduce decision-making subjectivity, and ensure the rationality and safety of the operation plan. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 is a flowchart of a digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene 3D model provided by an embodiment of the present invention;

[0048] Figure 2 is an architecture diagram of a digital decision-making and scheme generation system for uninterrupted power supply operations in a distribution network provided by an embodiment of the present invention.

[0049] Figure 3 is a block diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0050] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0051] In the power system sector, live-line work on distribution networks is a core component in ensuring power supply reliability, directly impacting the electricity user experience and the stable operation of social production and daily life. With the continuous expansion of the power grid and the steady growth of electricity demand, the complexity of distribution network lines is constantly increasing, and the environment along the line corridors is becoming increasingly diverse. Traditional live-line work modes are no longer adequate for the high-efficiency and safe operational requirements of the new era, and their inherent shortcomings are gradually becoming key bottlenecks restricting the quality and efficiency of operations.

[0052] Currently, traditional live-line work on power distribution networks mainly relies on two-dimensional drawings, tabular data, and the on-site memory of workers. This approach has significant limitations in complex line corridor scenarios. On the one hand, two-dimensional data cannot intuitively, comprehensively, and accurately reproduce the three-dimensional spatial relationship between the line and its surrounding environment, resulting in abstract operational information, easily creating information blind spots, and increasing the risk of misjudgment during the operation, thus posing a threat to operational safety. On the other hand, the selection of operational methods highly depends on the experience and judgment of senior workers, lacking quantitative data support and multi-scheme comparative analysis, making the decision-making process highly subjective and difficult to ensure the rationality and optimization of the operational plan.

[0053] To address the pain points of traditional operation modes, there is an urgent need for a technical solution that can overcome the limitations of two-dimensional presentation and achieve digital and scientific operation decision-making, solving problems such as insufficient reconstruction of three-dimensional spatial relationships of power lines and subjective decision-making in operation plans. Based on this, this invention provides a method and system for digital decision-making and plan generation for live-line work in distribution networks based on a real-world 3D model. It constructs a realistic operation scenario carrier through digital technology, establishes a standardized decision-making and plan generation process, compensates for the shortcomings of traditional operation modes, and enables efficient, safe, and scientific live-line work in distribution networks.

[0054] The various embodiments of the present invention will be described in detail below.

[0055] Please refer to Figure 1. This embodiment provides a method for digital decision-making and scheme generation for power distribution network uninterrupted operation based on a real-scene 3D model, including the following steps:

[0056] S11: Obtain multi-source spatial data and equipment service attribute data of distribution network lines, construct a three-dimensional digital twin scene based on the multi-source spatial data, and associate and match the equipment service attribute data with the spatial objects in the three-dimensional digital twin scene.

[0057] It should be noted that multi-source spatial data refers to various spatially related data used to construct a 3D scene of the distribution network lines. Equipment service attribute data, on the other hand, is service-related data concerning the equipment associated with the distribution network lines, used to give the equipment in the 3D scene practical operational and maintenance significance. The 3D digital twin scene is a 3D virtual scene built based on multi-source spatial data, consistent with the actual distribution network line scene, and can intuitively present the spatial distribution relationship of equipment. Spatial objects are the virtual carriers corresponding to the distribution network lines and equipment in the 3D digital twin scene.

[0058] In this step, by acquiring the spatial data and equipment service data required by the distribution network lines, a three-dimensional digital twin scene that recreates the actual scene is first built using the spatial data. Then, the equipment service attribute data is associated with the virtual spatial objects in the scene one by one, so that the three-dimensional scene not only has an intuitive spatial presentation capability, but also carries the service information of the equipment.

[0059] S12: Receive the task information input by the user and locate the corresponding position in the 3D digital twin scene.

[0060] It should be noted that the task information refers to the user-inputted instructions and requirements for live-line power distribution work. Location refers to matching the user-inputted task information with spatial objects in the 3D digital twin scene to determine the specific virtual spatial location of the task, thus establishing a correspondence between the virtual scene and the actual work object.

[0061] In this step, by receiving the task information input by the user, the features related to spatial location are extracted, the corresponding spatial objects are found and located in the constructed 3D digital twin scene, and the specific area and object of the task are identified.

[0062] S13: Retrieve the preset task method knowledge base and select several preliminary candidate task methods that match the current task.

[0063] It should be noted that the work method knowledge base is a pre-set database storing various live-line work methods for power distribution networks, including feasible work methods corresponding to different work scenarios. The preliminary candidate work methods are several work methods selected from the work method knowledge base that are compatible with the currently input work task information.

[0064] In this step, a pre-set knowledge base of job methods is retrieved. By matching the characteristics of the current job task with the applicable scenarios of various job methods in the knowledge base, several preliminary candidate job methods that meet the task requirements are selected.

[0065] S14: Simulate the implementation process of each preliminary candidate operation method in a three-dimensional digital twin scene, and perform dynamic safety distance verification and feasibility analysis to select candidate operation methods that meet the requirements.

[0066] It should be noted that the operation simulation is performed in a 3D digital twin scenario, virtually recreating the complete operational flow of each preliminary candidate operation method and intuitively presenting the interaction between personnel, machinery, and equipment during the operation. Dynamic safety distance verification is a process that detects and verifies the distance between personnel, machinery, and surrounding equipment in real time during the operation simulation to ensure compliance with safety regulations. Feasibility analysis is the process of analyzing the operability of each preliminary candidate operation method in a real-world scenario, combining the results of the operation simulation and dynamic safety distance verification. Candidate operation methods that meet the requirements are determined to be safe and feasible after dynamic safety distance verification and feasibility analysis.

[0067] In this step, the intuitiveness and simulability of the 3D digital twin scene are used to virtually simulate each preliminary candidate operation method selected in the previous step. During the simulation, dynamic safety distance verification is carried out simultaneously to ensure that the operation process meets safety requirements. At the same time, a feasibility analysis is conducted to determine whether the method can be implemented in actual operation. Finally, safe and feasible candidate operation methods are selected.

[0068] S15: Quantitatively evaluate and compare the candidate operation methods that meet the requirements, and generate a recommended solution sequence.

[0069] It should be noted that quantitative evaluation and selection refers to the process of objectively scoring and comparing candidate operation methods that meet the requirements using preset quantitative standards. This eliminates subjective judgment and improves the scientific nature of decision-making. The recommended solution sequence refers to the list of solutions formed by arranging the candidate operation methods that meet the requirements in order of their superiority or inferiority based on the results of the quantitative evaluation and selection.

[0070] In this step, the comprehensive performance of each solution is objectively evaluated and compared using preset quantitative evaluation standards, based on the safe and feasible candidate operation methods selected in the previous step. The solutions are ranked according to their merits based on the evaluation results, and a recommended solution sequence is generated to help users quickly locate the optimal or relatively optimal operation solution and improve the scientificity and efficiency of decision-making.

[0071] S16: Fill in the information of the recommended scheme sequence according to the preset report template data format to generate a preliminary work implementation plan report.

[0072] It should be noted that the report template data format is a pre-defined, standardized work implementation plan report format. The preliminary work implementation plan report is a draft of the work plan with a complete structure, formed by filling in the relevant information of the recommended plan sequence according to the pre-defined template format, and includes the core information of the recommended plan.

[0073] In this step, by calling a preset unified report template, the core information (such as the order of the schemes, the core content of each scheme, etc.) in the recommended scheme sequence is automatically extracted and filled in according to the template format to quickly generate a preliminary work implementation plan report.

[0074] S17: Receive user feedback on the preliminary work implementation plan report, including review, modification, and confirmation, and save the final plan to complete the digital decision-making and plan generation for power distribution network uninterrupted operation.

[0075] It should be noted that the review, modification, and confirmation information refers to the user's review of the preliminary work implementation plan report, the provision of modification opinions, and the final confirmation of the plan, along with related operational and feedback information. The final plan, on the other hand, is the distribution network live-line work plan that has been reviewed, modified, and confirmed by the user and is ready for direct use in on-site operations.

[0076] In this step, by receiving user instructions to review, modify, and confirm the preliminary report, the preliminary work implementation plan report is improved to ensure that the plan meets the actual work requirements; after confirming that there are no errors, the final plan is saved, thereby completing the digital decision-making and implementation of the power distribution network live-line work.

[0077] The method provided in this embodiment first constructs a three-dimensional virtual carrier that recreates the actual scene using data. Then, based on this scene, it completes the work positioning, candidate method screening, work process simulation, and safety verification. Through quantitative evaluation, it optimizes and ranks the solutions, automatically generates a standardized report, and combines it with manual review and confirmation for improvement. The entire process does not rely on blind judgment based on human experience, which not only ensures the safety, feasibility, and scientific nature of the work plan, but also realizes the digitalization, standardization, and efficiency of work decision-making and solution generation. It effectively improves the efficiency of power distribution network live-line work decision-making and the reliability of the solution. At the same time, the manual review and confirmation process takes into account both the convenience of digitalization and the flexibility of actual operation, forming a digital decision-making system that balances efficiency and practicality.

[0078] The digital decision-making and scheme generation method for live-line work in power distribution networks of the present invention can be implemented based on a layered architecture, mainly including a data acquisition and processing layer, a data layer, a service layer (engine layer), and an application layer. The data layer is responsible for storing multi-source data and business attribute data; the service layer provides core services such as 3D visualization, spatial analysis, and decision reasoning; and the application layer implements functions such as human-computer interaction and report generation.

[0079] The following describes some other embodiments of the present invention.

[0080] In one embodiment of the present invention, the multi-source spatial data includes image data acquired by UAV oblique photography, spatial point cloud data acquired by laser point cloud scanning, and digital image data; the equipment business attribute data includes equipment specification parameter data, commissioning date data, and wire connection point coordinate data.

[0081] In this embodiment, the multi-source spatial data specifically includes image data acquired by UAV oblique photography, spatial point cloud data acquired by laser point cloud scanning, and digital image data. The UAV can be a quadcopter equipped with a 5-lens oblique photography camera (24mm focal length, 20MP), flying at an altitude of 100m, with a forward overlap of 80% and a lateral overlap of 70%, achieving an image resolution of 2cm. The laser point cloud data is processed by PointCloud software, with classification thresholds set (ground point elevation difference < 0.3m, vegetation point reflectivity < 50%). Traverse point extraction uses a "curvature filtering algorithm" (curvature > 0.5 / m is considered a traverse). The tower model is generated through skeleton extraction and texture mapping. Digital image data serves as a supplement, enhancing the texture realism of the 3D model. After processing by realistic 3D modeling software, this multi-source spatial data can generate a realistic 3D model with centimeter-level precision. Simultaneously, a seven-parameter method is used to transform the WGS84 coordinate system to the local 2000 coordinate system, with the transformation error controlled within ±5cm, achieving coordinate unification. The equipment business attribute data specifically includes equipment specification parameters (such as conductor type, insulator type, tower type, etc.), commissioning date data, and line connection point coordinate data. This data mainly comes from PMS (Production Management System) ledgers, tower tables, conductor tables, and equipment tables in the digital twin business database. After being integrated with the real-scene 3D model, a digital twin with business attributes is formed. Furthermore, the 3D model uses AI image recognition algorithms to automatically identify, segment, and semantically label key objects such as conductors, insulators, switches, trees, and buildings, making them intelligent objects that can be understood and processed by computers, rather than simply a collection of triangular faces. It is important to clarify that the real-scene 3D model is the basic spatial carrier of the 3D digital twin scene, used only to recreate the actual spatial form of the distribution network lines; the 3D digital twin scene, based on the real-scene 3D model, further associates equipment business attribute data, possessing capabilities such as spatial visualization, interactive operation, and data linkage.

[0082] In one embodiment of the present invention, the task information includes a task route identifier, a tower number, a task type, and a target phase; locating the corresponding position in the three-dimensional digital twin scene includes:

[0083] S21: Extract the operation route identifier, tower number, operation type and target phase from the operation task information as positioning features.

[0084] The system includes a work line identifier to define the specific work line area, a tower number to locate the work tower, and work type (e.g., replacing insulators, connecting conductors) and target phase (e.g., A phase, C phase) to further pinpoint the work location and ensure the location does not deviate from the work requirements. Work task information is input via the system's web user interface, allowing users to select towers on the map, select conductor segments, etc., and supplementary information such as the line name can also be entered.

[0085] S22: Compare and match the positioning features with the spatial location identifiers of each spatial object in the 3D digital twin scene.

[0086] In this 3D digital twin scenario, spatial objects are associated with equipment business attribute information such as line identification, tower number, and equipment phase. This attribute information can be stored in a multi-source data center at the data layer. This data center not only integrates the 3D model library but also incorporates real-time data from PMS systems, GIS (Geographic Information System), meteorological systems, etc. Through data governance, a standardized and unified 3D information database is formed. Through feature comparison, spatial objects corresponding to the operation tasks can be quickly associated, avoiding positioning errors.

[0087] S23: Based on the matched spatial object, locate the corresponding tower and working area.

[0088] When the corresponding tower and work area are located, a 3D visualization service can be invoked at the same time. This service is based on WebGL technology (such as Cesium.js and Three.js engines) to achieve high-performance 3D model rendering and browsing on the browser side, and automatically switches the 3D scene view to the tower and work area to present the equipment environment and spatial relationships around the work area (such as the span between adjacent towers, the distribution of surrounding obstacles, etc.).

[0089] In this embodiment, the operation location is quickly located through the process of feature extraction and comparison matching, which solves the problems of vague positioning and low efficiency in traditional operation. This ensures that all subsequent operation simulations and decision analyses are carried out around the located operation area, thereby improving the accuracy of decision-making.

[0090] In one embodiment of the present invention, the work method knowledge base stores the applicable voltage levels, applicable working condition descriptions, required tools and equipment, and standard working hours for various power distribution network live-line work methods; several preliminary candidate work methods that meet the current work task are selected, including:

[0091] S31: Based on the operation line identifier, tower number, operation type and target phase in the operation task information, perform fuzzy matching with the applicable voltage level and applicable working condition description in the operation method knowledge base, and select operation methods with a suitability that meet the preset threshold as preliminary candidate operation methods.

[0092] The work method knowledge base stores detailed information on various live-line work methods for power distribution networks, including work method ID, name, applicable voltage level, applicable working condition description, required tools, and standard working hours. Fuzzy matching can cover similar scenarios in the working condition description (such as the compatibility of narrow urban passages with urban work). Preset thresholds are used to control the accuracy of the initial screening, avoiding the selection of too many unsuitable work methods while retaining potentially suitable solutions. This screening process can be executed by the decision reasoning engine of the service layer. The engine first extracts working condition data such as 3D environment, equipment type, adjacent tower span, and traffic conditions based on task location, and then matches it with the knowledge base.

[0093] S32: Extract the required tools and standard working hours for each preliminary candidate operation method.

[0094] The required tool and equipment information provides support for subsequent work feasibility analysis (such as tool and equipment compatibility and whether the work space meets the tool and equipment deployment requirements), while the standard working hours serve as the basic data for the work duration index in the subsequent quantitative evaluation, ensuring that the selected preliminary candidate work methods not only adapt to the working conditions but also provide the data required for subsequent analysis.

[0095] In this embodiment, preliminary candidate solutions that are suitable for the current task are selected from the task method knowledge base, and data required for subsequent processes are extracted. This not only ensures the efficiency of the selection process, but also provides data support for subsequent simulation verification and quantitative evaluation, avoids invalid task methods from entering subsequent complex processes, and reduces the system's computing costs.

[0096] In one embodiment of the present invention, dynamic safety distance verification and feasibility analysis are performed, including:

[0097] S41: Extract the motion trajectory coordinates of personnel and equipment during the implementation of each preliminary candidate operation method. Combine the spatial coordinates of the charged body and grounded body in the three-dimensional digital twin scene, and use the preset distance calculation rules to calculate the minimum distance data between each point on the motion trajectory and the charged body and grounded body.

[0098] The motion trajectory is obtained through 3D scene simulation (e.g., extraction from BIM model skeletal animation). Pre-defined distance calculation rules employ bounding box hierarchical detection and precise Euclidean distance calculation. First, non-collision objects are quickly eliminated using axis-aligned bounding boxes (AABB). Then, the minimum distance between vertices / edges / faces of candidate objects is calculated with an accuracy of ±1cm. Simultaneously, a dynamic buffer is created for the operator (or robotic arm) model. This buffer is a 3D spatial volume centered on its range of motion, updated in real-time based on a spherical expansion algorithm. Assuming the trajectory point coordinates are (x(t), y(t), z(t)) and the buffer radius r = 0.7m + 0.1 × wind speed (m / s), the 3D spatial volume is generated as follows:

[0099] The dynamic updating of the buffer ensures the real-time nature of the safety distance verification.

[0100] S42: Retrieve the safe distance threshold data and meteorological correction coefficient data for the corresponding voltage level, correct the minimum distance data, and conduct a comprehensive analysis in conjunction with the feasibility requirements of the operation. If the corrected minimum distance data is not less than the safe distance threshold and meets the feasibility requirements, select the corresponding candidate operation method; otherwise, remove the corresponding preliminary candidate operation method.

[0101] The safety distance threshold data and meteorological correction coefficient data are sourced from the safety rule table in the digital twin business database of the data layer, while the meteorological data comes from real-time meteorological system data integrated by the data center. The meteorological correction coefficient is used to adjust the safety distance requirements under different meteorological conditions (such as the impact of wind speed on the buffer radius). Operational feasibility requirements include tool compatibility, sufficient operating space, and clearance conditions. Clearance analysis is used to determine whether there are obstacles in the space under the conductor or around the equipment within a specific height range. Dynamic safety distance verification is performed by the dynamic safety distance verification algorithm in the service layer space analysis engine. This algorithm has a built-in algorithmic model of safety regulations and can provide real-time visual warnings. If the corrected minimum distance is less than the safety threshold, a high-key alarm will be triggered and the violation point will be recorded. In addition, this step also includes parallel simulation of the implementation process of each candidate operation method to achieve simultaneous verification of multiple schemes and improve verification efficiency.

[0102] In this embodiment, by using dynamic safety distance verification (covering the entire process of personnel and equipment movement), combined with meteorological correction and feasibility analysis, schemes that pose safety risks and cannot be implemented in practice are eliminated, providing a safe and feasible basic candidate set for subsequent quantitative evaluation.

[0103] In one embodiment of the present invention, a quantitative evaluation and comparison of candidate job methods that meet the requirements is performed to generate a recommended solution sequence, including:

[0104] S51: Extract several evaluation index data corresponding to each candidate operation method that meets the requirements.

[0105] The evaluation indicators include safety margin, operation time, cost, equipment reliability, and power supply impact. These data are derived from preliminary simulations (e.g., operation time, safety margin), a work method knowledge base (e.g., standard working hours), and a digital twin business database (e.g., equipment reliability parameters, environmental risk point data), covering dimensions such as safety, efficiency, cost, and reliability. The safety margin score is calculated using the formula (D...). actual -D safe ) / D safe ×100, if the result is <0, score 0 directly, D actual D is the minimum distance after dynamic verification. safe This is the safe distance threshold.

[0106] S52: Retrieve the preset weight data of each evaluation indicator, standardize the data of each evaluation indicator, and then sum them up by weight to obtain the comprehensive evaluation score data of each candidate operation method.

[0107] The weights were determined using the Analytic Hierarchy Process (AHP), with five senior operators scoring the indicators to determine the final weights: safety margin (w1=0.4), operation time (w2=0.2), cost (w3=0.2), equipment reliability (w4=0.1), and power supply impact (w5=0.1). Standardization was used to eliminate differences in the units of measurement for different indicators (such as different units for operation time and cost). The weighted summation formula is S=w1×(safety margin score)+w2×(1 / simulated operation time)+w3×(1 / simulated cost)+w4×(equipment reliability score)+w5×(power supply impact score), which reflects the overall merits of each candidate solution.

[0108] S53: Based on the comprehensive evaluation score data, sort from high to low and generate a sequence of recommended solutions.

[0109] The higher the score, the better the overall solution. The advantages and disadvantages of each solution (such as high risk, low cost, high efficiency, etc.) are also marked to provide users with a clear reference for decision-making. Solutions with lower scores but room for optimization can be marked as "needs optimization before adoption". Solutions with too high risk and no room for optimization are marked as "not recommended".

[0110] In this embodiment, by using multi-dimensional evaluation indicators, reasonable weight allocation, and standardized calculation, the bias of subjective judgment is avoided, and a sequence of recommended solutions with clear priorities is generated to help users quickly select the optimal operation solution and improve the scientific nature and efficiency of decision-making.

[0111] In one embodiment of the present invention, information of the recommended scheme sequence is filled in according to a preset report template data format to generate a preliminary work implementation plan report, including:

[0112] S61: Extract the process data, required tool and equipment configuration data, safety control data, risk point data, and simulation process screenshot data of each scheme in the recommended scheme sequence.

[0113] The process data corresponds to the implementation steps of the work method; the required tool configuration data comes from the work method knowledge base; the safety control data and risk point data come from the dynamic safety distance verification process (such as highlighted alarm violation points, locations with insufficient safety distance, etc.); and the simulation process screenshot data comes from the 3D scene simulation (such as scene screenshots when risk points occur, and screenshots of key nodes in the entire work simulation process). These data together constitute the content of the report, ensuring the completeness and usability of the report. Data extraction is achieved through an internal RESTful API, with the application layer's solution report generation module calling relevant data from the service layer and data layer.

[0114] S62: According to the bookmark identifiers and content format requirements in the pre-set report template data, match the various types of data extracted from the recommended scheme sequence to the corresponding positions to generate a preliminary work implementation plan report.

[0115] The pre-set report template can be in Word (.docx) format, containing fixed titles, paragraphs, tables, and predefined bookmarks and content controls. The system uses libraries such as Apache POI (Java) or python-docx (Python) to match and populate data with bookmarks, thereby automatically generating the report. The populated data includes task information, recommended solution details, comprehensive score, risk point tips, simulation screenshots, etc. The generated report is a standardized version with both text and images.

[0116] This embodiment enables the rapid and standardized generation of work implementation plan reports. By automatically extracting data and matching templates for filling, it avoids the tediousness and errors of manual report writing, improves report generation efficiency, and ensures that the report format is standardized, the content is detailed, and includes all the information required for the work.

[0117] In addition, a web user interface (UI) is provided for users to review, modify, and confirm the generated reports. Users can modify the content in the web UI or in the downloaded Word report. All manual modification records are kept, realizing intelligent human-machine collaboration. At the same time, the optimization experience (such as risk control measures) modified by users can be prompted by the system to be included in the work method knowledge base, so as to optimize the system's analysis model and realize the system's self-learning ability.

[0118] The following describes specific implementations of the present invention with some examples.

[0119] Example 1: A power supply company needs to replace a broken pin insulator on pole #36 of a 10kV line.

[0120] 1) Task input: The user clicks on pole #36 on the system map and selects the "Replace Insulator" task from the right-click menu.

[0121] 2) Data retrieval: The system background calls the 3D scene, locates pole #36, and queries the database to obtain that the pole is a Φ190×12m cement pole, the conductor is JKLYJ-10 / 95, the insulator is P-15T, the adjacent span is 85 meters, the site passage is farmland, but there is a low voltage line erected on the same pole.

[0122] 3) Solution decision: The decision engine matches feasible solutions from the knowledge base: Solution M1 (insulated bucket truck) and Solution M2 (insulated scaffolding + insulated gloves operation).

[0123] Simulation M1: The system simulates the entry path and working position of the insulated bucket truck in a 3D model. The spatial analysis engine calculates that when the bucket is at maximum extension, the distance between personnel inside the bucket and the high-voltage power line and the low-voltage line on the same pole is greater than 0.7m, and the verification is successful. The estimated cost is X yuan, and the estimated working time is Y hours.

[0124] Simulated M2: Simulated erection of insulated scaffolding. Spatial analysis revealed that the distance between the workers' activity space and the low-voltage line was only 0.4m, triggering a verification alarm. The system automatically marked this scheme as "high-risk," significantly reducing its score.

[0125] 4) Output results: The decision engine recommends M1 (insulated bucket truck) as the optimal solution, with a comprehensive score of 95 points.

[0126] 5) Report generation: When the user clicks “Generate Report”, the system will automatically fill in the corresponding positions of the report template with data such as #36 pole, insulated bucket truck, risk points (note to maintain a distance of >0.7m from the low-voltage line), and simulation diagram, and generate a preliminary “Implementation Plan for Live Operation of Insulator Replacement on #36 Pole of 10kV Line”.

[0127] 6) Manual optimization: The user checks the report and, based on on-site experience, manually adds "Insulating blankets need to be prepared to shield the low-voltage lines" to the "Tools and Equipment Preparation" column. The system saves this modification record.

[0128] Example 2: Connection of the drain line to pole #28 of the 10kV line.

[0129] 1) Task input: The user selects the conductor segment between pole #28 and the adjacent pole #29 in the 3D scene, selects the "Connect the guide wire" task, and the system automatically retrieves the 3D model of the area and marks the relevant information: conductor model JKLYJ-10 / 120, span 70m, and there is a two-story residential building nearby.

[0130] 2) Solution selection: The decision engine matched three solutions: M3 (insulated bucket truck), M4 (insulated platform), and M5 (drone-assisted operation).

[0131] 3) Three-dimensional simulation and verification:

[0132] M3: The simulated bucket truck is parked 3m east of the residential building and extended to the work point. The distance between the buffer and the residential building is 1.2m (>0.5m safety value), and the distance between the buffer and the live wire is 0.8m (>0.7m). The test is passed.

[0133] M4: During the simulation of building an insulated platform, it was found that the distance between the platform support and the balcony of a residential building was 0.3m (<0.5m), which triggered an alarm and marked it as "medium risk".

[0134] M5: The drone was used to simulate operation with a guide wire clamp. The minimum distance between the flight trajectory and the guide wire was calculated to be 0.6m (<0.7m), and the verification failed.

[0135] 4) Quantitative assessment: M3 scored 92 points overall (85 points for safety margin, 1.5 hours for duration, and Y yuan for cost), while M4 scored 75 points. Therefore, M3 is recommended.

[0136] 5) Report generation: Automatically fill in information such as the parking coordinates of the boom truck, the risk warning "avoid residential balconies", and simulation screenshots to generate the "Drainage Line Connection Operation Plan".

[0137] Example 3: Application of digital decision-making and scheme generation method for power distribution network uninterrupted operation in connection and diversion line operation in complex urban environment.

[0138] 1) Task Background and Input: A municipal power supply company plans to perform live-line connection work on pole #18 of the 10kV Chengdong line to ensure power supply access for a new residential area. Pole #18 is located next to a narrow street in the old city, with a complex surrounding environment: tall roadside trees (camphor trees) on the sidewalk, and communication fiber optic cables and street light lines running on the same pole, limiting the working space. The workers accurately locate pole #18 on the map of the system's web user interface, select the "connecting current line" task from the task list, and input the necessary additional information, such as the line name, pole number, and target phase (C phase).

[0139] 2) Data Fusion and Scene Construction: Upon receiving the task instruction, the system immediately calls the following multi-source data from the data layer for fusion: The real-scene 3D model database loads the oblique photogrammetric 3D model (OSGB format) of the area, clearly presenting the real spatial relationships of streets, trees, and buildings; the digital twin business database queries the pole table to obtain the precise latitude, longitude, height, and model of pole #18; queries the conductor table to obtain the model, rated current, and precise sag data calculated from point cloud data for the main line and the connecting line to be connected; and queries the environmental risk point table to obtain the identification, historical distance records, and estimated growth rate of the adjacent roadside trees. The spatial analysis engine performs integrated rendering of the above data in the 3D visualization service (Cesium.js engine), presenting users with a high-precision digital twin scene containing all business attributes and environmental risks, and automatically positioning the viewpoint to pole #18.

[0140] 3) Intelligent solution simulation and decision-making:

[0141] a. Preliminary screening of solutions: The decision reasoning engine accesses the work method knowledge base and automatically filters out two candidate solutions based on key working condition descriptions such as "10kV", "connecting the diversion line", and "narrow passage in the urban area": ​​Solution M1 (operation of insulated bucket truck) and Solution M2 (operation of insulated scaffolding combined with insulated gloves).

[0142] b. Three-dimensional simulation and dynamic verification:

[0143] Simulation M1: The system simulates a standard-sized insulated bucket truck in a 3D scene. The operator controls the virtual bucket truck via the UI to drive from the road and attempt to find the optimal working position. The spatial analysis engine activates a dynamic safety distance verification algorithm to calculate the space required for the bucket truck's outriggers to extend. It is found that the outriggers occupy part of the sidewalk, but the simulation shows that the requirement can be met by setting warning cones. The simulation raises the bucket to the working height and calculates the range of motion of the operator's arms inside the bucket (a dynamically changing cylindrical buffer space). The engine calculates in real time the distance between this buffer space and the 10kV live conductor and the communication optical cable on the same pole (considered as a grounding body). The verification finds that when approaching the working point, the minimum dynamic distance between the operator and the B-phase live conductor is 0.65 meters. The system immediately triggers an alarm because this value is less than the 0.7-meter safety distance threshold set for 10kV lines in the safety rule table. The alarm information and the highlighted risk point are recorded.

[0144] Simulation M2: The system switches to scheme M2 to simulate the construction of insulated scaffolding. The engine performs a clearance analysis and finds that the top of the scaffolding platform is too close to the street light line, posing a collision risk; at the same time, when simulating the operation of workers, the minimum distance between their activity range and the tree trunk is only 0.3 meters, triggering another dynamic safety check alarm.

[0145] c. Quantitative Evaluation and Comparison: The decision engine uses a quantitative evaluation model to score the two options. Option M1, due to its main risk of slightly insufficient dynamic distance (0.65m vs 0.7m), received more deductions in safety-related items, but its efficiency and cost advantages were significant, resulting in a comprehensive score of 72. Option M2, due to multiple risks and low operational efficiency, received a comprehensive score of 55. The engine did not simply discard M1, but based on the logic of "slight overshoot can be optimized," it retained it in the recommended sequence, but marked it as "needs optimization before adoption," while M2 was marked as "not recommended."

[0146] 4) Report generation and human-computer collaboration optimization:

[0147] d. Automatic Report Generation: The user selects "Generate M1 Optimization Plan Report". The plan report generation module starts, obtains all data of pole #18, M1 plan simulation data, risk point screenshots (highlighted in red at the moment when the distance is less than 0.65 meters), and scoring results through the internal API; calls the Apache POI library to open the preset "Live Connection Drainage Line Operation Plan.docx" template; automatically fills the data into the predefined bookmark positions in the template, such as ${optimal_method}->"Insulated Bucket Truck Operation (Requires Optimization)", ${risk_point}->"Minimum Dynamic Distance between Operator and Phase B Conductor 0.65 meters, Less Than 0.7 Meters of Safe Distance", and inserts risk screenshots, instantly generating a detailed preliminary plan report.

[0148] e. Manual Review and Optimization: After reviewing the report, the experienced supervisor manually adds the following to the "Risk Control Measures" section in the system's "Report Editing View": "Install insulating sleeves on phase B conductors to compensate for the 0.05-meter safety margin deficiency." This modification is recorded and saved by the system, forming the final solution. Simultaneously, the system prompts the supervisor to "Add to Knowledge Base" for this optimization measure. After confirmation, the system will automatically recommend "Installing Insulating Sleeves" as an optimization suggestion for similar operating conditions in the future.

[0149] Based on the foregoing embodiments and examples, it is clear that the advantages of the present invention compared to the prior art are as follows:

[0150] 1) Scientific and quantitative decision-making to eliminate the risk of empiricism: Break away from the reliance of traditional solutions on personal experience, and transform various influencing factors into calculable indicators through built-in engines and quantitative models. Provide objective and unified standards for multi-dimensional quantitative scoring and ranking of candidate solutions, thereby improving the safety and scientific nature of operations.

[0151] 2) Work plan rehearsal and risk pre-emptive assessment to achieve inherent safety: The entire work process is simulated in a high-fidelity digital twin environment, and the minimum distance between personnel, equipment and hazard sources is dynamically calculated to identify dynamic risks in advance. At the same time, the feasibility of equipment entry is verified to avoid waste of on-site resources.

[0152] 3) Leapfrog improvement in efficiency and optimized allocation of resources: Significantly reduce the time spent on processes such as exploration and scheme preparation, automatically generate standardized reports, accurately estimate resource needs, achieve reasonable allocation, and reduce waste.

[0153] 4) Knowledge accumulation and system self-evolution to form a smart empowerment platform: excellent work methods and expert experience are solidified into the knowledge base, and the system continuously learns through user feedback, optimizes models, enriches the knowledge base, and achieves self-evolution.

[0154] 5) Full-element digital management and visual collaboration: Based on the 3D model, the entire corridor is managed in an integrated and visual manner, providing a unified communication basis for personnel at all levels, improving collaboration efficiency and reducing information ambiguity.

[0155] Based on the same inventive concept, this application also provides a system for generating digital decision-making and solutions for live-line work in distribution networks based on real-scene 3D models, used to implement the aforementioned method for generating digital decision-making and solutions for live-line work in distribution networks based on real-scene 3D models. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations in the embodiments of the system for generating digital decision-making and solutions for live-line work in distribution networks based on real-scene 3D models provided below can be found in the limitations of the method for generating digital decision-making and solutions for live-line work in distribution networks based on real-scene 3D models described above, and will not be repeated here.

[0156] This invention also provides a digital decision-making and scheme generation system for power distribution network uninterrupted operation based on a real-scene 3D model, comprising:

[0157] The 3D digital twin scene construction unit is used to acquire multi-source spatial data and equipment service attribute data of distribution network lines, construct a 3D digital twin scene based on the multi-source spatial data, and associate and match the equipment service attribute data with the spatial objects in the 3D digital twin scene.

[0158] The task receiving unit is used to receive task information input by the user and locate the corresponding position in the 3D digital twin scene;

[0159] The preliminary candidate method screening unit is used to retrieve a preset task method knowledge base and screen out several preliminary candidate task methods that match the current task.

[0160] The candidate method simulation implementation unit is used to simulate the implementation process of each preliminary candidate operation method in a three-dimensional digital twin scene, and to perform dynamic safety distance verification and feasibility analysis to screen out the candidate operation methods that meet the requirements.

[0161] The recommended solution sequence generation unit is used to quantitatively evaluate and compare candidate job methods that meet the requirements, and generate a recommended solution sequence.

[0162] The preliminary plan report generation unit is used to fill in the information of the recommended plan sequence according to the preset report template data format and generate a preliminary work implementation plan report;

[0163] The final solution generation unit is used to receive user feedback on the preliminary work implementation plan report, including review, modification, and confirmation information, and to save the final solution, thus completing the digital decision-making and solution generation for power distribution network live-line work.

[0164] Furthermore, the multi-source spatial data includes image data collected by UAV oblique photography, spatial point cloud data collected by laser point cloud scanning, and digital image data; the equipment business attribute data includes equipment specification parameter data, commissioning date data, and wire connection point coordinate data.

[0165] Furthermore, the task information includes the task route identifier, tower number, task type, and target phase; and it is located to the corresponding position in the 3D digital twin scene, including:

[0166] Extract the operation route identifier, tower number, operation type, and target phase from the operation task information as positioning features;

[0167] The positioning features are compared and matched with the spatial location identifiers of each spatial object in the 3D digital twin scene;

[0168] Based on the matched spatial objects, the corresponding tower and work area are located.

[0169] Furthermore, the work method knowledge base stores the applicable voltage levels, applicable working condition descriptions, required tools and equipment, and standard working hours for various live-line work methods in distribution networks; it then filters out several preliminary candidate work methods that match the current work task, including:

[0170] Based on the work line identifier, tower number, work type and target phase in the work task information, fuzzy matching is performed with the applicable voltage level and applicable working condition description in the work method knowledge base to select work methods whose adaptability meets the preset threshold as preliminary candidate work methods.

[0171] Extract the required tools and standard working hours for each preliminary candidate operation method.

[0172] Furthermore, dynamic safety distance verification and feasibility analysis are conducted, including:

[0173] Extract the motion trajectory coordinates of personnel and equipment during the implementation of each preliminary candidate operation method, combine them with the spatial coordinates of charged and grounded bodies in the three-dimensional digital twin scene, and use the preset distance calculation rules to calculate the minimum distance data between each point on the motion trajectory and the charged and grounded bodies;

[0174] Retrieve the safety distance threshold data and meteorological correction coefficient data for the corresponding voltage level, correct the minimum distance data, and conduct a comprehensive analysis in conjunction with the operational feasibility requirements. If the corrected minimum distance data is not less than the safety distance threshold and meets the feasibility requirements, the corresponding candidate operation method is selected; otherwise, the corresponding preliminary candidate operation method is eliminated.

[0175] Furthermore, the candidate operation methods that meet the requirements are quantitatively evaluated and compared to generate a recommended solution sequence, including:

[0176] Extract several evaluation index data corresponding to each candidate operation method that meets the requirements;

[0177] Retrieve the preset weight data of each evaluation indicator, standardize the data of each evaluation indicator, and then sum them up by weight to obtain the comprehensive evaluation score data of each candidate operation method.

[0178] Based on the comprehensive evaluation scores, the recommended solutions are generated by sorting them from high to low.

[0179] Furthermore, following the pre-set report template data format, the information of the recommended scheme sequence is filled in to generate a preliminary work implementation plan report, including:

[0180] Extract process data, required tool configuration data, safety control data, risk point data, and simulation process screenshot data for each scheme in the recommended scheme sequence;

[0181] Based on the bookmarks and content format requirements in the pre-set report template data, the various types of data extracted from the recommended scheme sequence are matched to the corresponding positions to generate a preliminary work implementation plan report.

[0182] The above embodiments, from the perspective of core functional units, elucidate the overall functional architecture and the role and execution logic of the distribution network live-line operation digital decision-making and solution generation system based on a real-scene 3D model, clarifying the core functional modules and their collaborative operation relationships for realizing digital decision-making and solution generation for distribution network live-line operations. To translate the above functional unit architecture into an engineering-deployable system implementation scheme adapted to the actual operational needs of the distribution network, this invention further proposes a layered architecture design scheme for the system, considering the technical characteristics of distribution network operations, data management requirements, and human-computer interaction scenarios. The data sources, processing logic, technical support, and functional implementation details of each layer are clearly defined. Specific implementation methods are as follows:

[0183] As shown in Figure 2, the system adopts a layered architecture, mainly including a data acquisition and processing layer, a data layer, a service layer / engine layer, and an application layer. The details of each layer are as follows: The data acquisition and processing layer's data sources include multi-source spatial data, as well as existing PMS system ledger data, GIS geographic information data, and meteorological data. The data processing method refers to the aforementioned embodiments. The core of data fusion is to fuse and associate the real-scene 3D model, vector line model, and equipment attribute data through coordinate system transformation to form a digital twin. The data layer includes a real-scene 3D model database (storing 3D model files in formats such as OSGB and 3D Tiles), a digital twin business database (containing various structured tables), a safety rule table, an environmental risk point table, etc., providing data support for the entire system. The service layer includes 3D visualization services, a spatial analysis engine, and a decision reasoning engine, as well as additional functions of the spatial analysis engine such as distance measurement and clearance analysis, fully supporting the functional implementation of each embodiment. The application layer includes report generation and 3D visualization, as well as Web UI functions such as a scheme list view and a report editing view, improving the human-computer interaction experience.

[0184] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments 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. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0185] Referring to Figure 3, this embodiment of the invention also provides a computer device, including: a memory and a processor, and a computer program stored in the memory. When the computer program is executed on the processor, it implements the digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene three-dimensional model as described in any of the above methods.

[0186] The computer device may be a desktop computer, laptop, handheld computer, or cloud server, etc. This computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that Figure 3 is merely an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0187] The processor referred to can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0188] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard drive or RAM. In other embodiments, the memory may be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory may include both internal and external storage units of the computer device. The memory is used to store the operating system, applications, boot loader, data, and other programs, such as the program code of the computer program. The memory can also be used to temporarily store data that has been output or will be output.

[0189] This invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is run by a processor, it implements the digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene 3D model, as described in any of the above methods.

[0190] In this embodiment, if the integrated unit 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, all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0191] This invention provides a computer program product, including a computer program that, when executed by a processor, implements the digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene 3D model, as described in any of the above methods.

[0192] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0193] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0194] In the embodiments disclosed in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and 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 displayed or discussed mutual coupling or direct coupling or communication connection may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0195] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for digital decision-making and scheme generation for live-line work in distribution networks based on real-scene 3D models, characterized in that, The process includes the following steps: acquiring multi-source spatial data and equipment service attribute data of the distribution network lines; constructing a three-dimensional digital twin scene based on the multi-source spatial data; and associating and matching the equipment service attribute data with spatial objects in the three-dimensional digital twin scene; receiving user-inputted task information and locating the corresponding position in the three-dimensional digital twin scene; and retrieving a preset task method knowledge base to select several preliminary candidate task methods that match the current task. The implementation process of each preliminary candidate operation method is simulated in the three-dimensional digital twin scene, and dynamic safety distance verification and feasibility analysis are performed to screen out the candidate operation methods that meet the requirements. The candidate operation methods that meet the requirements are quantitatively evaluated and compared to generate a recommended solution sequence; the information of the recommended solution sequence is filled in according to the preset report template data format to generate a preliminary operation implementation plan report; Receive user feedback on the preliminary work implementation plan report, including review, modification, and confirmation, and save the final plan to complete the digital decision-making and plan generation for power distribution network uninterrupted operation.

2. The method for digital decision-making and scheme generation for live-line work in distribution networks based on a real-scene 3D model according to claim 1, characterized in that, The multi-source spatial data includes image data acquired by UAV oblique photography, spatial point cloud data acquired by laser point cloud scanning, and digital image data; the equipment business attribute data includes equipment specification parameter data, commissioning date data, and wire connection point coordinate data.

3. The method for digital decision-making and scheme generation for live-line work in distribution networks based on a real-scene 3D model according to claim 1, characterized in that, The task information includes the task route identifier, tower number, task type, and target phase; Locating the corresponding location in the three-dimensional digital twin scene includes: extracting the operation route identifier, tower number, operation type and target phase from the operation task information as positioning features; The positioning features are compared and matched with the spatial location identifiers of each spatial object in the three-dimensional digital twin scene; based on the matched spatial objects, the corresponding towers and working areas are located.

4. The method for digital decision-making and scheme generation for live-line work in distribution networks based on a real-scene 3D model according to claim 3, characterized in that, The work method knowledge base stores the applicable voltage levels, applicable working condition descriptions, required tools and equipment, and standard working hours for various power distribution network live-line work methods. Several preliminary candidate operation methods that meet the current operation task are selected, including: based on the operation line identifier, tower number, operation type and target phase in the operation task information, fuzzy matching is performed with the applicable voltage level and applicable working condition description in the operation method knowledge base, and operation methods with a suitability that meets a preset threshold are selected as preliminary candidate operation methods. Extract the required tools and standard working hours for each preliminary candidate operation method.

5. The method for digital decision-making and scheme generation for live-line work in distribution networks based on a real-scene 3D model according to claim 1, characterized in that, Dynamic safety distance verification and feasibility analysis are performed, including: extracting the motion trajectory coordinates of personnel and equipment during the implementation of each preliminary candidate operation method; combining the spatial coordinates of the live and grounded bodies in the three-dimensional digital twin scene; using preset distance calculation rules to calculate the minimum distance data between each point on the motion trajectory and the live and grounded bodies; retrieving the safety distance threshold data and meteorological correction coefficient data under the corresponding voltage level; correcting the minimum distance data; and conducting a comprehensive analysis in conjunction with the operation feasibility requirements. If the corrected minimum distance data is not less than the safety distance threshold and meets the feasibility requirements, the corresponding candidate operation method is selected; otherwise, the corresponding preliminary candidate operation method is eliminated.

6. The method for digital decision-making and scheme generation for live-line work in distribution networks based on a real-scene 3D model according to claim 1, characterized in that, The candidate job methods that meet the requirements are quantitatively evaluated and compared to generate a recommended solution sequence, including: extracting several evaluation index data corresponding to each candidate job method that meets the requirements; retrieving the preset weight data of each evaluation index, standardizing each evaluation index data and then weighting and summing it to obtain the comprehensive evaluation score data of each candidate job method; and sorting the comprehensive evaluation score data from high to low to generate a recommended solution sequence.

7. The method for digital decision-making and scheme generation for live-line work in distribution networks based on a real-scene 3D model according to claim 1, characterized in that, According to the preset report template data format, the information of the recommended scheme sequence is filled in to generate a preliminary work implementation plan report, including: extracting the process data, required tool and equipment configuration data, safety control data, risk point data and simulation process screenshot data of each scheme in the recommended scheme sequence; matching the various types of data extracted from the recommended scheme sequence to the corresponding positions according to the bookmarks and content format requirements in the preset report template data to generate the preliminary work implementation plan report.

8. A digital decision-making and scheme generation system for live-line work in distribution networks based on real-scene 3D models, characterized in that, include: A three-dimensional digital twin scene construction unit is used to acquire multi-source spatial data and equipment service attribute data of distribution network lines, construct a three-dimensional digital twin scene based on the multi-source spatial data, and associate and match the equipment service attribute data with spatial objects in the three-dimensional digital twin scene; The task receiving unit is used to receive task information input by the user and locate the corresponding position in the three-dimensional digital twin scene; the preliminary candidate method filtering unit is used to retrieve a preset task method knowledge base and filter out several preliminary candidate task methods that meet the current task. The candidate method simulation implementation unit is used to simulate the implementation process of each preliminary candidate operation method in the three-dimensional digital twin scene, and to perform dynamic safety distance verification and feasibility analysis to screen out the candidate operation methods that meet the requirements. The recommended solution sequence generation unit is used to quantitatively evaluate and compare the candidate operation methods that meet the requirements, and generate a recommended solution sequence; the preliminary solution report generation unit is used to fill in the information of the recommended solution sequence according to the preset report template data format, and generate a preliminary operation implementation plan report. The final solution generation unit is used to receive the user's review, modification and confirmation information on the preliminary work implementation plan report, and save the final solution to complete the digital decision-making and solution generation for power distribution network uninterrupted operation.

9. A computer device, characterized in that, The device includes a processor and a memory: the memory is used to store computer programs and send the instructions of the computer programs to the processor; the processor executes, according to the instructions of the computer programs, a digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene three-dimensional model as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, which, when executed by a processor, implements a digital decision-making and scheme generation method for power distribution network uninterrupted operation based on a real-scene three-dimensional model as described in any one of claims 1-7.

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