A distribution network defect hidden danger cross-region coordination management system and method

Abstract

The application discloses a kind of distribution network defect hidden danger cross-regional collaborative management system and method, system includes inventory system data empowerment module, area grading and hidden danger classification module, cross-regional collaborative scheduling module and management execution and feedback module;Through inventory system data empowerment module, the standardization adaptation activation of existing distribution network inventory system original data and idle interface is completed, constructs the basic data set of distribution network defect hidden danger shared across regions, is completed by area grading and hidden danger classification module scientific grading, defect hidden danger standard classification and management priority quantization sequencing, relies on cross-regional collaborative scheduling module and realizes the accurate matching of cross-regional operation and maintenance resources and defect hidden danger and generates standardization collaborative management instruction, finally through management execution and feedback module, defect hidden danger field disposal and process data acquisition feedback are completed, the application does not need to reconstruct business process, realizes the accurate matching of operation and maintenance resources and defect hidden danger, improves hidden danger disposal efficiency and management quality effect.

Description

Technical Field

[0001] This invention relates to the field of operation and maintenance management and digital collaborative governance technology of power distribution network equipment, and in particular to a cross-regional collaborative governance system and method for power distribution network defects and hidden dangers. Background Technology

[0002] Timely detection and closed-loop management of distribution network defects and hidden dangers are core aspects of ensuring the safe and stable operation of the power grid and improving power supply reliability. In recent years, the State Grid Corporation of China has continuously promoted a special action to improve the quality and efficiency of distribution network operation and maintenance, issuing a series of documents that clearly require strengthening the whole-process management and control of distribution network defects and hidden dangers, and relying on the power supply service command system to achieve digital management and control of distribution network operation and maintenance business at the provincial, municipal, county, and team levels. Currently, the power supply service command system has realized basic functions such as defect and hidden danger work order entry, review, and archiving, and is widely used in distribution network operation and maintenance scenarios of power grid companies in various provinces and cities across the country.

[0003] The current management of distribution network defects and hidden dangers still faces many industry pain points: First, the management model is mainly based on independent handling in a single region and at a single level. There are significant differences in operation and maintenance capabilities between provinces, cities, counties, and work teams. Remote cities, counties, and work teams lack operation and maintenance resources and have weak professional capabilities, making it impossible to quickly handle emergency defects and hidden dangers. Cross-regional resource allocation relies entirely on manual coordination, resulting in extremely low response efficiency. Second, the problem of data silos in existing systems is prominent. Data from existing systems such as the power supply service command system, the power grid resource business platform, and the distribution automation system are mostly closed loops within the region. There is no standardized channel for cross-regional and cross-level data sharing, making it impossible to achieve accurate matching of operation and maintenance resources with defects and hidden dangers across the entire region. Third, existing management solutions lack a scientific priority division mechanism, which easily leads to problems such as untimely handling of emergency hidden dangers and excessive occupation and maintenance resources being occupied by general hidden dangers, making it difficult to guarantee the quality and efficiency of management. Fourth, the implementation of cross-regional collaborative management mostly relies on building new independent systems, which cannot reuse the interfaces, data, and business processes of existing systems. The transformation costs are high, the implementation cycle is long, and it is difficult to adapt to the information operation level of grassroots city and county company operation and maintenance personnel, resulting in low system practicality. Summary of the Invention

[0004] This invention addresses the industry pain points of slow response to independent handling of distribution network defects and hidden dangers in single areas, data silos in existing systems, and difficulties in matching cross-regional operation and maintenance resources. It provides a cross-regional collaborative governance system and method for distribution network defects and hidden dangers, which can reuse existing system resources, achieve precise matching of cross-regional operation and maintenance resources with defects and hidden dangers, and improve the efficiency and quality of hidden danger handling and governance.

[0005] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows: A cross-regional collaborative governance system for distribution network defects and hidden dangers includes a system data empowerment module, a regional classification and hidden danger classification module, a cross-regional collaborative scheduling module, and a governance execution and feedback module. The system data empowerment module receives existing raw data and idle interface resources from the existing power supply service command system, power grid resource business platform, and distribution automation system. It performs standardized adaptation and activation processing on these resources, including deduplication, correlation fusion, and structuring of the raw data, and protocol adaptation and format unification activation processing of the idle interface resources. This results in a cross-regional shared basic dataset of distribution network defects and hidden dangers and a standardized interactive interface compatible with a four-level architecture (province-city-county-team). This dataset is then sent to the regional classification and hidden danger classification module. The regional classification and hidden danger classification module performs regional operation and maintenance capability classification and defect and hidden danger level classification on the basic dataset. It uses a fuzzy comprehensive evaluation method to complete the regional operation and maintenance capability classification and, based on the State Grid distribution network equipment defects and hidden dangers... The system classifies potential hazards according to the established criteria, then prioritizes their treatment using the analytic hierarchy process (AHP), resulting in a distribution network regional classification matrix, a list of defective hazards, and the priority of treatment based on these classifications. This matrix is ​​then sent to the cross-regional collaborative scheduling module. The cross-regional collaborative scheduling module performs cross-regional resource matching and scheduling strategy generation on the regional classification matrix, the list of defective hazards, and the priority of treatment results. It accurately matches surplus resources in the core area with resource gaps in the collaborative area, generates scheduling strategies based on equipment geographical topology, and converts them into standardized instructions. This results in cross-regional collaborative treatment instructions for distribution network defects and hazards, which are then sent to the treatment execution and feedback module. The treatment execution and feedback module executes these instructions and collects and provides feedback on the treatment process data. After parsing and verifying the instructions, it generates on-site handling task sheets, completes on-site hazard handling, and collects data on the handling process and results, obtaining the distribution network defect and hazard treatment execution results and on-site verification data.

[0006] Furthermore, the existing system data empowerment module includes an existing data access submodule, an interface adaptation and activation submodule, a shared dataset construction submodule, and a data security encryption submodule. The existing data access submodule receives raw existing data from the existing power supply service command system, power grid resource business platform, and distribution automation system, and sends it to the shared dataset construction submodule and the interface adaptation and activation submodule. The raw existing data includes defect and hazard work order data, medium-voltage equipment ledger data, equipment operating status data, and maintenance resource data, as well as historical equipment fault data, maintenance personnel professional skill level data, and regional maintenance material reserve data. The interface adaptation and activation submodule, based on the transmission protocol and interface format information of the raw existing data, performs protocol adaptation and data format unification activation processing on the idle data interfaces of the existing system. The system obtains a standardized interactive interface compatible with a four-level architecture of province-city-county-work team, enabling cross-regional data interoperability among existing systems. The shared dataset construction submodule performs deduplication, correlation fusion, and structured dataset construction processing on the existing raw data to obtain a cross-regional shared basic dataset of distribution network defects and hidden dangers, and sends it to the regional classification and hidden danger classification module and its own distributed data storage unit for persistent storage. The data security encryption submodule performs SM4 algorithm encryption and access permission level control processing on the cross-regional shared basic dataset of distribution network defects and hidden dangers and sensitive data transmitted between modules. It uses the SM4 symmetric encryption algorithm to encrypt the data, configures data access permissions according to the province-city-county-work team level, obtains the encrypted secure shared dataset, and opens it to the corresponding authorized operation and maintenance personnel.

[0007] Furthermore, the regional classification and hazard classification module includes a regional operation and maintenance capability assessment submodule, a defect and hazard level determination submodule, and a governance priority ranking submodule. The regional operation and maintenance capability assessment submodule performs fuzzy comprehensive evaluation on the regional operation and maintenance personnel quantity, professional skill level, operation and maintenance equipment configuration, and emergency material reserve data in the distribution network defect and hazard basic dataset. It constructs an operation and maintenance capability evaluation index system and assigns weights, calculates the capability score for each region through fuzzy comprehensive evaluation, obtains the distribution network regional classification matrix for core governance regions, collaborative governance regions, and auxiliary governance regions, and sends it to the governance priority ranking submodule. The defect and hazard level determination submodule... The submodule classifies the defect and hazard work order data and equipment operation status data in the distribution network defect and hazard basic dataset into emergency, general, and minor categories according to the State Grid distribution network equipment defect and hazard judgment standards, and obtains a defect and hazard classification list, which is then sent to the governance priority ranking submodule. The governance priority ranking submodule performs governance priority ranking processing on the distribution network regional hierarchical matrix and defect and hazard classification list using the analytic hierarchy process, constructs a regional capacity-hazard level dual-layer evaluation model, calculates the governance priority score of each hazard, obtains the hierarchical classification governance priority results of regional capacity and hazard level, and sends them to the cross-regional collaborative scheduling module.

[0008] Furthermore, the cross-regional collaborative scheduling module includes a cross-regional resource matching submodule, a scheduling strategy generation submodule, and a governance instruction issuance submodule. The cross-regional resource matching submodule performs precise resource matching between core and collaborative regions on the operation and maintenance resource data in the regional hierarchical matrix, governance priority results, and distribution network defect and hidden danger basic dataset. It statistically analyzes surplus operation and maintenance resources in the core governance region, identifies resource gaps in the collaborative governance region, completes one-to-one matching of resources and hidden dangers according to the priority of hidden dangers, obtains a cross-regional operation and maintenance resource allocation plan, and sends it to the scheduling strategy generation submodule. The scheduling strategy generation submodule analyzes the cross-regional operation and maintenance resource allocation plan and governance priority results, and... The geographical topology of the distribution network equipment is analyzed to generate scheduling strategies, clarifying the responsible parties for handling potential hazards, the time limits for handling, the resource allocation paths, and technical handling suggestions. This yields a cross-regional collaborative governance strategy for distribution network defects and hazards, which is then sent to the governance instruction issuance submodule. The governance instruction issuance submodule standardizes and hierarchically converts the cross-regional collaborative governance strategy into instructions, breaking down the strategy content into provincial-municipal-county-work team levels, generating standardized instruction formats adapted to each level, and obtaining cross-regional collaborative governance instructions for distribution network defects and hazards adapted to the four-level architecture. These instructions are then sent to the governance execution and feedback module, the corresponding level of the power supply service command system main station, and the mobile terminal of maintenance personnel.

[0009] Furthermore, the cross-regional resource matching submodule also supports cross-regional scheduling of emergency resources, automatically triggering a resource retrieval mechanism from surrounding collaborative regions when a sudden emergency hazard occurs. Specifically, when a sudden emergency defect hazard occurs in the core governance area and its own operation and maintenance resources are insufficient, the cross-regional resource matching submodule automatically scans the emergency resource reserve data of surrounding collaborative governance areas, quickly matches available emergency operation and maintenance personnel, maintenance equipment, and emergency supplies, generates an emergency cross-regional operation and maintenance resource allocation plan, and pushes it to the scheduling strategy generation submodule to prioritize the generation of emergency governance instructions, thereby realizing rapid cross-regional handling of emergency hazards.

[0010] Furthermore, the governance execution and feedback module includes a governance instruction receiving submodule, a field execution submodule, and a process data feedback submodule. The governance instruction receiving submodule parses and verifies the cross-regional collaborative governance instructions, analyzing the disposal requirements, responsible parties, and time limits in the instructions, verifying the matching of the instructions with the actual field conditions, obtaining an actionable field disposal task sheet, and sending it to the field execution submodule. The field execution submodule, based on the field disposal task sheet, completes the field disposal of distribution network defects and hazards, and simultaneously performs data collection and processing on the field disposal process, collecting on-site photos, disposal operation records, hazard elimination verification data, resource usage records, and other on-site verification data, and sending it to the process data feedback submodule. The process data feedback submodule encrypts and standardizes the on-site verification data and the governance execution results of hazard disposal completion / incomplete / overdue, using the SM4 algorithm to encrypt sensitive data, encapsulating the data content according to a preset format, obtaining a standardized governance process feedback data packet, and sending it to the existing system data empowerment module to update the existing defect and hazard work order data.

[0011] Furthermore, the collaborative governance system also includes an effect evaluation and iterative optimization module; the effect evaluation and iterative optimization module includes a governance effect quantitative evaluation submodule, a strategy parameter optimization submodule, and an existing system adaptation and update submodule; the governance effect quantitative evaluation submodule receives the distribution network defect and hidden danger governance execution results and on-site verification data sent by the governance execution and feedback module, performs multi-indicator quantitative evaluation processing on it, and uses defect and hidden danger elimination rate, cross-regional governance response time, governance completion timeliness rate, and hidden danger recurrence rate as core evaluation indicators, calculates the actual values ​​of each indicator and compares them with preset assessment thresholds to obtain the quantitative evaluation results of the cross-regional collaborative governance of distribution network defects and hidden dangers, and sends them to the strategy parameter optimization submodule; the strategy parameter optimization submodule classifies and categorizes the governance effect quantitative evaluation results. The reverse optimization and adjustment process for categories and scheduling parameters involves adjusting the regional operation and maintenance capability assessment weights, defect and hidden danger level judgment thresholds, cross-regional resource matching rules, and scheduling strategy generation parameters for evaluation indicators that fail to meet the standards. This yields optimized regional classification rules, hidden danger classification standards, and collaborative scheduling parameters, which are then sent back to the regional classification and hidden danger classification module and the cross-regional collaborative scheduling module, respectively. Based on the optimized regional classification rules, hidden danger classification standards, and collaborative scheduling parameters, the existing system adaptation and update submodule updates the shared dataset construction rules and interface adaptation standards of the existing system data empowerment module. This involves adjusting the field filtering, association rules, and interface protocol adaptation parameters of the dataset to obtain an updated existing system adaptation scheme, achieving synchronous iteration between the existing system and the collaborative governance strategy.

[0012] Furthermore, the multi-indicator quantitative evaluation process specifically involves: using the defect and hazard elimination rate, cross-regional governance response time, governance completion timeliness rate, and hazard recurrence rate as core evaluation indicators, calculating the actual values ​​of each indicator and comparing them with preset assessment thresholds; the preset assessment thresholds include a defect and hazard elimination rate ≥98%, a cross-regional governance response time ≤2 hours, a general hazard governance completion timeliness rate ≥95%, an emergency hazard governance completion timeliness rate 100%, and a hazard recurrence rate ≤1%. When the actual value of any indicator fails to reach the preset assessment threshold, the strategy parameter optimization submodule automatically triggers the parameter reverse optimization adjustment process.

[0013] Furthermore, the collaborative governance system also includes a cross-regional visualization monitoring module. This module performs geographic topology mapping and chart visualization transformation on the distribution network regional hierarchical matrix, defect and hidden danger classification list, cross-regional collaborative governance instructions, governance execution results, and quantitative evaluation results of governance effects. It maps the hidden danger data and regional data to the distribution network geographic topology map and converts the evaluation results into visual charts such as bar charts, line charts, and pie charts, obtaining a panoramic monitoring result of cross-regional collaborative governance of distribution network defects and hidden dangers. This provides provincial and municipal level operation and maintenance management personnel with a visualized service for hierarchical viewing, real-time monitoring, and manual intervention. The regional visualization monitoring module integrates a cross-regional governance early warning sub-module. This sub-module compares the governance execution results and on-site verification data with preset cross-regional governance assessment thresholds, which correspond to the assessment standards of the State Grid's special action to improve the quality and efficiency of distribution network operation and maintenance. When situations such as overdue defect and hidden danger governance, delays in cross-regional resource allocation, or hidden danger recurrence rates exceeding the threshold occur, an abnormal early warning information for cross-regional collaborative governance of distribution network defects and hidden dangers is automatically generated and pushed to the mobile terminals of the corresponding level of operation and maintenance management personnel and the main station of the power supply service command system, while simultaneously triggering manual supervision and reminder instructions.

[0014] A method for cross-regional collaborative management of distribution network defects and hidden dangers, applied to the aforementioned cross-regional collaborative management system for distribution network defects and hidden dangers, includes the following steps: S1. The existing system data empowerment module receives the existing raw data and idle interface resources of the existing power supply service command system, power grid resource business platform, and distribution automation system, performs standardized adaptation and activation processing on them, and obtains a cross-regional shared distribution network defect and hidden danger basic dataset and a standardized interactive interface compatible with the four-level architecture of province-city-county-team, and sends it to the regional classification and hidden danger classification module. S2. The regional hierarchical and hidden danger classification module performs regional operation and maintenance capability hierarchical and defect and hidden danger level classification processing on the basic dataset of distribution network defects and hidden dangers to obtain the distribution network regional hierarchical matrix, defect and hidden danger classification list and hierarchical classification and governance priority results, and sends them to the cross-regional collaborative scheduling module. S3. The cross-regional collaborative scheduling module performs cross-regional resource matching and scheduling strategy generation processing on the regional hierarchical matrix, the defect and hidden danger classification list and the governance priority result to obtain the cross-regional collaborative governance instruction for distribution network defects and hidden dangers, and sends it to the governance execution and feedback module. S4. The governance execution and feedback module performs instruction implementation and governance process data collection and feedback processing on the cross-regional collaborative governance instructions to obtain the governance execution results of distribution network defects and hidden dangers and on-site verification data.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention, through a two-tiered design of regional hierarchical and hazard classification, achieves automated and precise matching of surplus operation and maintenance resources in core governance areas with resource gaps in collaborative governance areas. It constructs a standardized and process-oriented cross-regional collaborative handling mechanism, completely resolving the industry pain points of traditional manual cross-regional coordination response delays and non-standardized processes. It enables rapid cross-regional response and closed-loop handling of emergency defects and hazards, fully meeting the assessment requirements of the State Grid's special action to improve the quality and efficiency of distribution network operation and maintenance. It effectively addresses the core issues of insufficient operation and maintenance capabilities and untimely handling of emergency hazards in remote cities and counties. Through the existing system data empowerment module, it can fully reuse the idle interface capabilities and data resources of existing power supply service command systems, power grid resource business platforms, and other existing systems. It eliminates the need to build a new independent cross-regional governance system, reconstruct existing distribution network operation and maintenance business processes, and interrupt the normal operation of existing systems. Compared with traditional new system transformation schemes, it significantly reduces project construction investment, greatly shortens the project implementation cycle, and can quickly adapt to the existing digital system architecture of the State Grid, without requiring large-scale replacement of hardware and software equipment at the grassroots level.

[0016] This invention employs fuzzy comprehensive evaluation to scientifically classify regional operation and maintenance capabilities, strictly adheres to the State Grid's standards for managing distribution network equipment defects and hidden dangers to classify hazard levels, and combines the analytic hierarchy process (AHP) to quantitatively prioritize governance. It constructs a precise control system that prioritizes the handling of emergency hazards, coordinates the handling of general hazards, and addresses minor hazards locally. This significantly improves the closed-loop handling rate of distribution network defects and hidden dangers, effectively reduces the probability of recurrence of similar hazards, and fully meets the core requirements of distribution network operation and maintenance quality and efficiency management. Furthermore, this invention constructs a fully automated handling system encompassing data access, automatic classification and grading, automatic strategy generation, standardized instruction issuance, and execution feedback. It eliminates the need for grassroots operation and maintenance personnel to conduct complex cross-regional coordination, multi-dimensional data statistical analysis, and manual judgment of governance priorities. They only need to execute standardized on-site handling tasks, significantly reducing the information technology operation skills required of grassroots operation and maintenance personnel in city and county companies, greatly improving the efficiency of related work, and effectively solving the core pain points of large statistical reporting errors and heavy workload for grassroots personnel. Attached Figure Description

[0017] Figure 1 This is the overall architecture diagram of the cross-regional collaborative governance system for distribution network defects and hidden dangers of the present invention; Figure 2 This is a flowchart illustrating the implementation of the cross-regional collaborative governance method for distribution network defects and hidden dangers according to the present invention. Detailed Implementation

[0018] To facilitate understanding of the present invention, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Those skilled in the art should understand that the embodiments described are merely illustrative of the invention and should not be considered as specific limitations thereof.

[0019] In the following description of the embodiments, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted so as not to obscure the description of this application with unnecessary detail.

[0020] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of a described feature, integral, step, operation, element, and / or component, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof. It should also be understood that, as used in this specification and the appended claims, the term "and / or" refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0021] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0022] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance. References to "one embodiment" or "some embodiments" in this application mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized. System Implementation Example:

[0023] This embodiment uses the State Grid provincial power company as the application scenario, covering the provincial company and its eight subordinate municipal power supply companies. It is built upon the already operational power supply service command system, power grid resource business platform, and distribution automation system, and is adapted to a four-level operation and maintenance architecture of province-municipal-county-team. Figure 1 As shown, the specific implementation is as follows: Existing System Data Empowerment Module: The existing system data empowerment module receives existing raw data and idle interface resources from the existing power supply service command system, power grid resource business platform and distribution automation system, performs standardized adaptation and activation processing on them, and obtains a basic dataset of distribution network defects and hidden dangers that can be shared across regions and a standardized interactive interface compatible with the four-level architecture of province-city-county-team, and sends it to the regional classification and hidden danger classification module.

[0024] The existing system data empowerment module includes an existing data access submodule, an interface adaptation and activation submodule, a shared dataset construction submodule, and a data security encryption submodule. The existing data access submodule, through interface adaptation, accesses defect and hazard work order data from the existing power supply service command system, medium-voltage equipment ledger data from the power grid resource business platform, equipment operation status data from the distribution automation system, and user power outage information data from the marketing business system. It also accesses operation and maintenance resource data such as regional maintenance personnel, maintenance equipment, and emergency supplies, with data formats strictly adhering to the State Grid CIM unified model standard. The interface adaptation and activation submodule adapts idle data interfaces of the existing system to HTTP and MQTT protocols and unifies data formats, generating standardized interactive interfaces compatible with a four-level architecture to achieve cross-regional data interoperability. The shared dataset construction submodule deduplicates, correlates, merges, and constructs data from the original data. The data processing employs the 3σ criterion to remove outliers, eliminating invalid data exceeding ±3 standard deviations of the equipment's rated parameters, and generating a basic dataset of distribution network defects and potential hazards for cross-regional sharing. The data security encryption submodule uses the SM4 national cryptographic algorithm to encrypt sensitive data transmitted across regions. The algorithm has a block length of 128 bits and a key length of 128 bits, performs 32 rounds of nonlinear iteration, and adopts the ECB working mode. At the same time, it configures hierarchical access permissions according to a four-level architecture: provincial company level has full data access permission, prefecture-level city level has data access permission for its own region and collaborative regions, county level has data access permission for its own region, and team level has only access permission for task-related data, fully ensuring the security of cross-regional data sharing.

[0025] Regional Classification and Hazard Classification Module: The regional classification and hazard classification module performs regional operation and maintenance capability classification and defect and hazard level classification on the basic dataset of distribution network defects and hazards, and obtains the distribution network regional classification matrix, defect and hazard classification list and classification management priority results, and sends them to the cross-regional collaborative scheduling module.

[0026] The regional grading and hazard classification module includes a regional operation and maintenance capability assessment submodule, a defect and hazard level determination submodule, and a governance priority ranking submodule. The regional operation and maintenance capability assessment submodule extracts operation and maintenance resource data from the basic dataset and uses fuzzy comprehensive evaluation to grade the operation and maintenance capabilities of each city-level company. It constructs an evaluation system with four primary indicators: personnel allocation (0.35 weight), equipment allocation (0.25 weight), material reserves (0.2 weight), and emergency response capability (0.2 weight). It also includes 12 secondary indicators, such as the number of operation and maintenance personnel, professional skill levels, maintenance equipment configuration, emergency material reserves, emergency response time, and historical success rate. A trapezoidal membership function is used to calculate membership degrees, and regions are divided into three levels based on comprehensive scores: ≥80 points for core governance regions, 60-80 points for collaborative governance regions, and <60 points for auxiliary governance regions. The analytic hierarchy process (AHP) is used to determine indicator weights, and the consistency ratio CR of the judgment matrix is ​​0.06 < 0.1, meeting the consistency verification requirements. Finally, a distribution network regional grading matrix is ​​generated. The defect and hazard level determination submodule... The stator module classifies defect and potential hazard work orders into three levels according to the State Grid distribution network equipment defect management regulations, specifying the time limits for handling each category: emergency defects ≤ 24 hours, general defects ≤ 7 days, and minor defects ≤ 30 days, generating a defect and potential hazard classification list. The governance priority ranking submodule uses the analytic hierarchy process (AHP) to construct a two-layer evaluation model of regional capability and hazard level. The weight of the first-level criterion is set as follows: hazard level 0.6, regional operation and maintenance capability 0.4; the weight of the sub-criterion is set as follows: hazard level dimension: emergency 0.7, general 0.2, minor 0.1; regional operation and maintenance capability dimension: insufficient capability 0.7, average capability 0.2, sufficient capability 0.1. The consistency ratio CR of the judgment matrix is ​​0.05 < 0.1, which meets the consistency verification requirements. Combining the regional hierarchical matrix and the hazard classification list, the governance priority of each defect and potential hazard is calculated, generating a hierarchical classification governance priority result.

[0027] Cross-regional collaborative scheduling module: The cross-regional collaborative scheduling module performs cross-regional resource matching and scheduling strategy generation processing on the regional hierarchical matrix, defect and hidden danger classification list and governance priority results to obtain cross-regional collaborative governance instructions for distribution network defects and hidden dangers, and sends them to the governance execution and feedback module.

[0028] The cross-regional collaborative scheduling module includes a cross-regional resource matching submodule, a scheduling strategy generation submodule, and a governance instruction issuance submodule. The cross-regional resource matching submodule receives the regional hierarchical matrix, governance priority results, and operation and maintenance resource data to accurately match surplus resources in the core area with resource gaps in collaborative / auxiliary areas, generating a cross-regional operation and maintenance resource allocation plan. For sudden and urgent defects and hidden dangers, it automatically triggers an emergency scheduling mechanism, scans emergency resources in surrounding collaborative areas, and generates an emergency resource allocation plan. The scheduling strategy generation submodule, based on the geographical topology of the distribution network equipment, clarifies the responsible party for handling hidden dangers, the handling time limit, resource allocation path, and technical handling suggestions, generating a cross-regional collaborative governance strategy. The governance instruction issuance submodule breaks down the strategy according to a four-level architecture, generates standardized hierarchical governance instructions, issues them to the governance execution and feedback module, and simultaneously pushes them to the corresponding level of the power supply service command system main station and the mobile terminals of operation and maintenance personnel.

[0029] Governance Execution and Feedback Module: The governance execution and feedback module implements the cross-regional collaborative governance instructions and collects and processes data during the governance process to obtain the governance execution results of distribution network defects and hidden dangers and on-site verification data.

[0030] The governance execution and feedback module includes a governance instruction receiving submodule, a field execution submodule, and a process data feedback submodule. The governance instruction receiving submodule receives cross-regional collaborative governance instructions, performs instruction parsing and operational condition verification, and generates actionable field handling task sheets. The field execution submodule receives task sheets, completes on-site handling of defects and hazards, and simultaneously collects on-site verification data such as on-site photos, handling operation records, hazard elimination verification data, and resource usage records. The process data feedback submodule encrypts and standardizes the governance execution results (including handling completed / incomplete / overdue status) and on-site verification data using the same SM4 national cryptographic algorithm as described above, and sends them to the effect evaluation and iterative optimization module via the cross-regional data exchange bus, while simultaneously updating the defect and hazard work order status of the existing system.

[0031] Effectiveness Evaluation and Iterative Optimization Module: This module is optional and includes a governance effectiveness quantitative evaluation submodule, a strategy parameter optimization submodule, and an existing system adaptation and update submodule. The governance effectiveness quantitative evaluation submodule receives governance execution results and on-site verification data, and completes the quantitative evaluation of governance effectiveness based on the aforementioned State Grid standard assessment requirements. The strategy parameter optimization submodule adjusts the regional operation and maintenance capability assessment weights, hazard level judgment thresholds, cross-regional resource matching rules, and scheduling strategy parameters for indicators that do not meet the assessment requirements, generating an optimized parameter set, which is then sent back to the regional classification and hazard classification module and the cross-regional collaborative scheduling module. The existing system adaptation and update submodule adjusts the dataset construction rules and interface adaptation standards of the existing system data empowerment module based on the optimized parameter set, completing the synchronous iteration of the existing system.

[0032] Cross-regional visual monitoring module: This optional module is built on a B / S architecture and supports two-level access control from the provincial to the municipal level. It maps defect and hidden danger data, regional classification results, governance instructions, and execution results to the distribution network geographic topology map, generating a panoramic monitoring interface for cross-regional governance of distribution network defects and hidden dangers. It also displays governance effect comparison curves and resource allocation status. The integrated cross-regional governance early warning sub-module automatically generates abnormal early warning information when situations such as governance overdue, resource allocation delays, or repeated occurrence of hidden dangers occur, which do not meet the assessment requirements. This information is pushed to the corresponding operation and maintenance management personnel and triggers manual supervision reminders.

[0033] Cross-regional data interaction bus: The cross-regional data interaction bus communicates with the existing system data empowerment module, the regional classification and hidden danger classification module, the cross-regional collaborative scheduling module, the governance execution and feedback module, the cross-regional visualization monitoring module, and the effect evaluation and iterative optimization module, respectively, to realize cross-level and cross-regional data interaction and command transmission between the modules. Method Implementation Examples:

[0034] This embodiment, based on the aforementioned system, uses the emergency defect handling of a 10kV line in a remote prefecture of the State Grid as the implementation scenario. This prefecture-level city was assessed as an area requiring auxiliary maintenance, with insufficient local maintenance personnel and emergency repair equipment. The affected line exhibited an emergency defect where the tower foundations were eroded by rainwater, posing a risk of pole collapse and power outage. Figure 2 As shown, the specific implementation steps are as follows: S1. The existing system data empowerment module accesses the defect and hidden danger work order data reported by the municipal company, the line operation data of the distribution automation system, and the equipment ledger data of the power grid resource business platform. At the same time, it accesses the emergency operation and maintenance team and maintenance equipment data of the municipal company in the core governance area. The data sampling period is set to 15 minutes, the data format follows the State Grid CIM unified model standard, abnormal data is removed by using the 3σ criterion, idle interfaces of the existing system are adapted and activated, data deduplication, correlation fusion and structured processing are completed, and a basic dataset of distribution network defects and hidden dangers is generated. Sensitive data is encrypted using the SM4 national cryptographic algorithm (128-bit block / key, 32 rounds of iteration, ECB mode) and then sent to the regional classification and hidden danger classification module.

[0035] S2, the regional classification and hazard classification module receives the basic dataset. Using fuzzy comprehensive evaluation, it identifies the affected city as the auxiliary governance area and the supporting city as the core governance area. The weights of the first-level indicators in the evaluation system are: personnel configuration 0.35, equipment configuration 0.25, material reserves 0.2, and emergency response capability 0.2. The consistency ratio of the judgment matrix CR = 0.06 < 0.1, meeting the verification requirements, and a regional classification matrix is ​​generated. Based on the State Grid defect management standards, the tower foundation scour defect is determined to be an emergency defect with a handling time limit of ≤ 24 hours, generating a defect hazard classification list. A two-layer evaluation model is constructed using the analytic hierarchy process. The weights of the first-level criteria are: hazard level 0.6 and regional operation and maintenance capability 0.4. The consistency ratio of the judgment matrix CR = 0.05 < 0.1, meeting the verification requirements, and the defect governance priority is calculated to be the highest level. The regional classification matrix, classification list, and priority results are sent to the cross-regional collaborative scheduling module.

[0036] S3, the cross-regional collaborative dispatch module receives input data, identifies the shortage of emergency repair equipment in the affected cities, matches the surplus emergency repair teams and dedicated repair equipment in the supporting cities, and generates a cross-regional emergency resource allocation plan; combined with the geographical topology of the lines, it clarifies the responsible parties for handling the situation, the 24-hour handling time limit, the personnel and equipment allocation routes, and the on-site handling technical requirements, and generates an emergency collaborative governance strategy; according to the four-level architecture of province-city-county-team, it generates standardized emergency governance instructions, issues them to the governance execution and feedback module, and pushes them to the power supply service command system of the affected and supporting cities and the mobile terminals of maintenance personnel.

[0037] The S4 governance execution and feedback module receives emergency governance instructions, parses and generates on-site handling task orders, supports municipal emergency repair teams to complete cross-regional assistance and on-site defect handling according to the task orders, and collects on-site handling photos, tower foundation repair verification data, resource usage records and other on-site verification data. The governance execution results and on-site verification data after defect handling are encrypted and standardized using the SM4 algorithm and sent to the effect evaluation and iterative optimization module, while simultaneously updating the defect work order status of the existing system.

[0038] The S5 module, which assesses and iterates the effectiveness of the treatment and the data from the field, receives the treatment results and the data from the field. The assessment shows that the entire process of handling this defect meets the State Grid's standard assessment requirements, the hidden dangers have been completely eliminated, and there is no risk of recurrence. The module incorporates the data on personnel deployment and treatment process into the algorithm sample library, optimizes the emergency resource matching rules for the affected area, and sends the optimized parameters back to the corresponding module. At the same time, it completes the adaptation and update of the existing system to form a closed-loop optimization. The visualization module displays the entire treatment process in real time, with no abnormal warnings triggered.

[0039] 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.

[0040] In various embodiments, the hardware implementation of the technology can directly utilize existing smart devices, including but not limited to industrial control computers, PCs, smartphones, handheld devices, and floor-standing devices. Its input device preferably uses an on-screen keyboard, its data storage and computing modules utilize existing memory, calculators, and controllers, its internal communication modules utilize existing communication ports and protocols, and its remote communication utilizes existing GPRS networks, the World Wide Web, etc.

[0041] 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 device 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.

[0042] In the embodiments provided by this invention, it should be understood that the disclosed apparatus / terminal devices and methods can be implemented in other ways. For example, the apparatus / terminal device 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 shown or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0043] In the various embodiments of the present invention, the functional units 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 units can be implemented in hardware or as software functional units. If the integrated module / 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, the present invention can implement all or part of the processes in the methods of the above embodiments, or it can be accomplished 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: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

Claims

1. A cross-regional collaborative governance system for distribution network defects and hidden dangers, characterized in that, The system includes a data empowerment module for existing systems, a regional classification and hazard classification module, a cross-regional collaborative scheduling module, and a governance execution and feedback module. The data empowerment module receives existing raw data and idle interface resources from the existing power supply service command system, power grid resource business platform, and distribution automation system. It performs standardized adaptation and activation processing to obtain a cross-regional shared basic dataset of distribution network defects and hazards, and a standardized interactive interface compatible with a four-level architecture (province-city-county-team). This dataset is then sent to the regional classification and hazard classification module. The regional classification and hazard classification module classifies the basic dataset of distribution network defects and hazards based on regional operation and maintenance capabilities. The system classifies and processes potential hazards to obtain a distribution network area hierarchical matrix, a list of defect and hazard classifications, and hierarchical classification and treatment priority results, which are then sent to the cross-regional collaborative scheduling module. The cross-regional collaborative scheduling module performs cross-regional resource matching and scheduling strategy generation processing on the area hierarchical matrix, the list of defect and hazard classifications, and the treatment priority results to obtain cross-regional collaborative treatment instructions for distribution network defects and hazards, which are then sent to the treatment execution and feedback module. The treatment execution and feedback module performs instruction implementation and treatment process data collection and feedback processing on the cross-regional collaborative treatment instructions to obtain distribution network defect and hazard treatment execution results and on-site verification data.

2. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 1, characterized in that, The existing system data empowerment module includes an existing data access submodule, an interface adaptation and activation submodule, a shared dataset construction submodule, and a data security encryption submodule. The existing data access submodule receives raw existing data from the existing power supply service command system, power grid resource business platform, and distribution automation system, and sends it to the shared dataset construction submodule and the interface adaptation and activation submodule. The raw existing data includes defect and hazard work order data, medium-voltage equipment ledger data, equipment operating status data, and maintenance resource data, as well as historical equipment fault data, maintenance personnel professional skill level data, and regional maintenance material reserve data. The interface adaptation and activation submodule, based on the transmission protocol and interface format information of the raw existing data, performs protocol adaptation and data format unification activation processing on the idle data interfaces of the existing system, obtaining a standardized interactive interface compatible with the four-level architecture of province-city-county-team, enabling cross-regional data interoperability among various existing systems. The shared dataset construction submodule performs deduplication, correlation fusion, and structured dataset construction processing on the existing raw data to obtain a cross-regional shared basic dataset of distribution network defects and hidden dangers. It then sends the dataset to the regional classification and hidden danger classification module and its own distributed data storage unit for persistent storage. The data security encryption submodule performs SM4 algorithm encryption and access permission level control processing on the cross-regional shared basic dataset of distribution network defects and hidden dangers and sensitive data transmitted between modules to obtain an encrypted secure shared dataset, which is then made available to authorized operation and maintenance personnel at the corresponding level.

3. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 1, characterized in that, The regional classification and hidden danger classification module includes a regional operation and maintenance capability assessment submodule, a defect and hidden danger level determination submodule, and a governance priority ranking submodule. The regional operation and maintenance capability assessment submodule performs fuzzy comprehensive evaluation on the regional operation and maintenance personnel number, professional skill level, operation and maintenance equipment configuration, and emergency material reserve data in the distribution network defect and hidden danger basic dataset to obtain a distribution network regional classification matrix of core governance area, collaborative governance area, and auxiliary governance area, and sends it to the governance priority ranking submodule. The defect hazard level determination submodule classifies the defect hazard work order data and equipment operation status data in the distribution network defect hazard basic dataset into emergency, general, and minor categories according to the State Grid distribution network equipment defect hazard determination standard, and obtains a defect hazard classification list, which is then sent to the governance priority ranking submodule. The governance priority ranking submodule performs governance priority ranking processing on the distribution network regional hierarchical matrix and defect hazard classification list using the analytic hierarchy process, obtains the hierarchical classification governance priority results of regional capacity and hazard level, and sends them to the cross-regional collaborative scheduling module.

4. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 1, characterized in that, The cross-regional collaborative scheduling module includes a cross-regional resource matching submodule, a scheduling strategy generation submodule, and a governance instruction issuance submodule. The cross-regional resource matching submodule performs precise resource matching processing between the core region and the collaborative region on the operation and maintenance resource data in the regional hierarchical matrix, governance priority results, and distribution network defect and hidden danger basic dataset to obtain a cross-regional operation and maintenance resource allocation plan, and sends it to the scheduling strategy generation submodule. The scheduling strategy generation submodule processes the cross-regional operation and maintenance resource allocation plan and governance priority results, combined with the geographical topology of the distribution network equipment, to generate a cross-regional collaborative governance strategy for distribution network defects and hidden dangers, and sends it to the governance instruction issuance submodule. The governance instruction issuance submodule performs standardized and hierarchical instruction conversion processing on the cross-regional collaborative governance strategy to obtain cross-regional collaborative governance instructions for distribution network defects and hidden dangers adapted to the four-level architecture, and sends them to the governance execution and feedback module and the corresponding level of the power supply service command system master station and the mobile terminal of operation and maintenance personnel.

5. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 4, characterized in that, The cross-regional resource matching submodule also supports cross-regional scheduling of emergency resources, automatically triggering a resource retrieval mechanism from surrounding collaborative regions when a sudden emergency hazard occurs. Specifically, when a sudden emergency hazard occurs in the core governance area and its own maintenance resources are insufficient, the cross-regional resource matching submodule automatically scans the emergency resource reserve data of surrounding collaborative governance areas, quickly matches available emergency maintenance personnel, repair equipment, and emergency supplies, generates an emergency cross-regional maintenance resource allocation plan, and pushes it to the scheduling strategy generation submodule to prioritize the generation of emergency governance instructions, thereby achieving rapid cross-regional handling of emergency hazards.

6. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 1, characterized in that, The governance execution and feedback module includes a governance instruction receiving submodule, an on-site execution submodule, and a process data feedback submodule. The governance instruction receiving submodule parses and verifies the cross-regional collaborative governance instructions to obtain an actionable on-site handling task sheet, and sends it to the on-site execution submodule. The on-site execution submodule, based on the on-site handling task order, completes the on-site handling of distribution network defects and hidden dangers. Simultaneously, it collects and processes data during the on-site handling process, including on-site photos, handling operation records, hidden danger elimination verification data, resource usage records, and other on-site verification data, and sends this data to the process data feedback submodule. The process data feedback submodule encrypts and standardizes the on-site verification data and the results of completed / incomplete / overdue handling of hidden dangers, creating a standardized governance process feedback data packet, which is then sent to the existing system data empowerment module to update the existing defect and hidden danger work order data.

7. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 1, characterized in that, The collaborative governance system also includes an effect evaluation and iterative optimization module. This module comprises a governance effect quantitative evaluation submodule, a strategy parameter optimization submodule, and an existing system adaptation and update submodule. The governance effect quantitative evaluation submodule receives the distribution network defect and hidden danger governance execution results and on-site verification data sent by the governance execution and feedback module, performs multi-indicator quantitative evaluation processing on them, obtains the cross-regional collaborative governance effect quantitative evaluation results for distribution network defects and hidden dangers, and sends them to the strategy parameter optimization submodule. The strategy parameter optimization submodule performs reverse optimization and adjustment processing on the governance effect quantitative evaluation results for hierarchical, classification, and scheduling parameters, obtaining optimized regional hierarchical rules, hidden danger classification standards, and collaborative scheduling parameters, and sends them back to the regional hierarchical and hidden danger classification module and the cross-regional collaborative scheduling module, respectively. The existing system adaptation and update submodule, based on the optimized regional hierarchical rules, hidden danger classification standards, and collaborative scheduling parameters, performs adaptation and update processing on the shared dataset construction rules and interface adaptation standards of the existing system data empowerment module, obtaining an updated existing system adaptation scheme, achieving synchronous iteration between the existing system and the collaborative governance strategy.

8. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 7, characterized in that, The multi-indicator quantitative evaluation process specifically involves: using the defect and hidden danger elimination rate, cross-regional governance response time, governance completion timeliness rate, and hidden danger recurrence rate as core evaluation indicators, calculating the actual values ​​of each indicator and comparing them with preset assessment thresholds; the preset assessment thresholds include defect and hidden danger elimination rate ≥98%, cross-regional governance response time ≤2 hours, general hidden danger governance completion timeliness rate ≥95%, emergency hidden danger governance completion timeliness rate 100%, and hidden danger recurrence rate ≤1%. When the actual value of any indicator fails to reach the preset assessment threshold, the strategy parameter optimization submodule automatically triggers the parameter reverse optimization adjustment process.

9. The cross-regional collaborative governance system for distribution network defects and hidden dangers according to claim 8, characterized in that, The collaborative governance system also includes a cross-regional visualization monitoring module. This module performs geographic topology mapping and chart visualization transformation on the distribution network regional hierarchical matrix, defect and hidden danger classification list, cross-regional collaborative governance instructions, governance execution results, and quantitative evaluation results of governance effects. This yields a panoramic monitoring result of cross-regional collaborative governance of distribution network defects and hidden dangers, providing provincial and municipal level operation and maintenance management personnel with visualized services for hierarchical viewing, real-time monitoring, and manual intervention. The cross-regional visualization monitoring module also integrates a cross-regional governance early warning sub-module. The cross-regional governance early warning submodule compares and judges the governance execution results and on-site verification data with the preset cross-regional governance assessment threshold, which corresponds to the assessment standards of the State Grid's special action to improve the quality and efficiency of distribution network operation and maintenance. When there are delays in the treatment of defects and hidden dangers, delays in cross-regional resource allocation, or when the recurrence rate of hidden dangers exceeds the threshold, an abnormal early warning information for cross-regional collaborative treatment of distribution network defects and hidden dangers will be automatically generated and pushed to the mobile terminal of the corresponding level of operation and maintenance management personnel and the main station of the power supply service command system, while triggering manual supervision and reminder instructions.

10. A method for cross-regional collaborative management of distribution network defects and hidden dangers, applied to the cross-regional collaborative management system for distribution network defects and hidden dangers as described in any one of claims 1-9, characterized in that, The method includes the following steps: S1. The existing system data empowerment module receives the existing raw data and idle interface resources of the existing power supply service command system, power grid resource business platform, and distribution automation system, performs standardized adaptation and activation processing on them, and obtains a cross-regional shared distribution network defect and hidden danger basic dataset and a standardized interactive interface compatible with the four-level architecture of province-city-county-team, and sends it to the regional classification and hidden danger classification module. S2. The regional hierarchical and hidden danger classification module performs regional operation and maintenance capability hierarchical and defect and hidden danger level classification processing on the basic dataset of distribution network defects and hidden dangers to obtain the distribution network regional hierarchical matrix, defect and hidden danger classification list and hierarchical classification and governance priority results, and sends them to the cross-regional collaborative scheduling module. S3. The cross-regional collaborative scheduling module performs cross-regional resource matching and scheduling strategy generation processing on the regional hierarchical matrix, the defect and hidden danger classification list and the governance priority result to obtain the cross-regional collaborative governance instruction for distribution network defects and hidden dangers, and sends it to the governance execution and feedback module. S4. The governance execution and feedback module performs instruction implementation and governance process data collection and feedback processing on the cross-regional collaborative governance instructions to obtain the governance execution results of distribution network defects and hidden dangers and on-site verification data.

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