Distribution network line interval monitoring graph information optimization method and device

Abstract

The invention relates to the technical field of distribution network scheduling and monitoring graph optimization, in particular to a distribution network line interval monitoring graph information optimization method and device, and the method comprises the steps: 1, data collection: obtaining multi-source data of a distribution network line, the multi-source data comprising line static archive data, real-time operation data, client side data and associated system data; 2, performing data fusion processing, performing standardized cleaning on the multi-source data, and establishing a data association mapping relation; 3, reconstructing monitoring graph information, and constructing an optimized distribution network line interval monitoring graph containing line basic information, customer influence analysis information and auxiliary decision-making information based on the fused data; and 4, dynamically updating, namely changing and refreshing the content of the monitoring graph and a decision recommendation result according to data change and client side information. According to the invention, distribution network fault studying and judging efficiency and handling speed can be improved, first-aid repair resource scheduling is optimized, and power supply reliability and user power utilization experience are improved.

Description

Technical Field

[0001] This invention relates to the field of distribution network scheduling and monitoring map optimization technology, and is a method and apparatus for optimizing monitoring map information of distribution network line bays. Background Technology

[0002] The current distribution network dispatching system, on which distribution network dispatching relies, suffers from a significant deficiency in its display of distribution network line bay diagrams, exhibiting a limited range of information. Existing systems can only present basic electrical parameters such as voltage, current, power, and protection status, lacking data on line physical characteristics and equipment lifecycle information. Key parameters such as line diameter, length, and load-bearing capacity are missing, making it difficult for dispatchers to accurately assess line load conditions and to quickly make effective decisions in overload or fault scenarios. Furthermore, the equipment's installation, operation, maintenance, and fault records are not linked to the bay diagrams, preventing dispatchers from timely understanding of equipment historical status and current operating conditions, severely hindering equipment health assessments and fault prediction.

[0003] Secondly, the system suffers from significant data silos. Data from multiple platforms involved in distribution network operation, including marketing systems, data acquisition systems, line loss systems, and power supply service command systems, has not been effectively integrated. Real-time meter status data from the data acquisition system cannot be accessed, making it difficult for dispatchers to monitor user electricity consumption and line load changes in real time. Customer electricity attributes from the marketing system, such as electricity type, consumption amount, and consumption time, are not correlated, affecting power supply planning and fault handling strategy optimization. Data on transformer equipment operating conditions from the line loss system is missing, making it difficult to monitor equipment operating status and manage line losses. Data from the power supply service command system, such as fault reporting records and repair progress, is not utilized, resulting in a lack of necessary information support during fault handling. Furthermore, static data such as equipment ledgers and historical fault records are not fully utilized, further restricting the comprehensiveness of dispatch decisions.

[0004] Furthermore, there are significant bottlenecks in operation and maintenance efficiency. Due to the limited information dimensions and data silos, fault diagnosis requires dispatchers to manually query data across multiple systems, which is time-consuming and prone to errors, reducing the accuracy and efficiency of fault diagnosis. Accident location relies excessively on dispatchers' manual experience, which is highly subjective and limited by individual capabilities, resulting in insufficient location accuracy and speed. The lack of data support for emergency repair resource scheduling makes it impossible to scientifically grasp information such as the location of emergency repair teams and the inventory of emergency repair materials, which can easily lead to resource waste and repair delays. The lack of customer-side data makes it impossible to fully consider customer needs and impacts when handling faults, prolonging the handling time, affecting users' normal power consumption experience, and also leading to low accident handling efficiency, prolonged power outage time, reduced power supply reliability, increased equipment maintenance difficulty and operation and maintenance costs, and causing user complaints and dissatisfaction, which seriously restricts the overall operation and maintenance quality and service level of the distribution network.

[0005] Specifically, existing technologies suffer from the following bottlenecks: When a fault occurs, dispatchers need to manually consult data from multiple systems and platforms, such as marketing systems, data acquisition systems, and line loss systems, to obtain the information required for fault assessment. This cross-system query method is not only time-consuming but also prone to errors, affecting the accuracy and efficiency of fault assessment. Due to the lack of comprehensive data support, fault location mainly relies on the dispatcher's manual experience and judgment. This method is not only highly subjective but also easily limited by the dispatcher's individual capabilities, resulting in low accuracy and efficiency in fault location. In terms of emergency repair resource scheduling, the current system lacks necessary data support, such as the location of emergency repair teams and the inventory of emergency repair materials. This makes it difficult for dispatchers to allocate emergency repair resources scientifically, potentially leading to waste of emergency repair resources and reduced repair efficiency. The dispatch system currently lacks relevant customer-side data, such as customers' electricity demand and electricity usage habits. This prevents dispatchers from fully considering customer needs and impacts when handling faults, resulting in slower fault response and disruption to users' normal electricity use.

[0006] Due to the aforementioned problems, the current distribution network line bay diagram has the following drawbacks in practical applications: When a fault occurs, dispatchers need to manually consult multiple data sources, leading to low efficiency in fault handling, prolonged power outage time, and reduced power supply reliability. The prolonged power outage time and reduced power supply reliability directly impact users' normal electricity experience, potentially triggering user complaints and dissatisfaction. The lack of comprehensive data support makes equipment maintenance and management difficult, potentially increasing equipment failure rates and maintenance costs. The low efficiency of operation and maintenance also increases operation and maintenance costs, including labor costs and material costs. Summary of the Invention

[0007] This invention provides a method and apparatus for optimizing monitoring map information of distribution network line intervals, which overcomes the shortcomings of the prior art and can effectively solve the problems of single information dimension, data silos, and low operation and maintenance efficiency in the existing distribution network dispatching system.

[0008] One of the technical solutions of this invention is achieved through the following measures: a method for optimizing distribution network line interval monitoring map information, comprising: Step 1, data acquisition: acquiring multi-source data of distribution network lines, wherein the multi-source data includes line static archive data, real-time operation data, customer-side data, and related system data; Step 2, data fusion processing: standardizing and cleaning the multi-source data, and establishing data association mapping relationships; Step 3, monitoring map information reconstruction: constructing an optimized distribution network line interval monitoring map based on the fused data, wherein the monitoring map includes basic line information, customer impact analysis information, and auxiliary decision-making information; Step 4, dynamic updating: updating the display content and decision recommendation results of the monitoring map in real time according to real-time data changes and changes in customer-side information.

[0009] The following are further optimizations and / or improvements to one of the above-mentioned technical solutions: In step one above, the static data of the line may include the line type, wire diameter, tower parameters and equipment service life; the real-time operation data may include current, voltage, load rate, switch status and meter readings; the customer-side data may include user level, electricity consumption type, contact information and power outage sensitivity; the associated system data may include the fault analysis results of the dispatching system, the work order information of the marketing system and the topology of the GIS system.

[0010] In step two above, the data association mapping relationship may include the binding relationship between customer-side data and line topology nodes, as well as the spatiotemporal alignment relationship between real-time operation data and static archive data; in step three, the basic line information may be the overlay display information of line static archive data and real-time operation data, the customer impact analysis information may include the level distribution information of line-covered users and the power outage impact range information, and the auxiliary decision-making information may include fault repair path planning information and load transfer scheme recommendation information.

[0011] In step two above, standardized cleaning may include standardizing data formats, removing outliers, and filling in missing values.

[0012] In step three above, the reconstruction of the monitoring chart information may also include the hierarchical display settings for basic line information, customer impact analysis information, and auxiliary decision-making information.

[0013] The second technical solution of the present invention is achieved through the following measures: a distribution network line interval monitoring map information optimization device, comprising: a multi-source data acquisition unit for acquiring multi-source data of distribution network lines, wherein the multi-source data includes line static archive data, real-time operation data, customer-side data, and related system data; a data fusion processing unit for standardizing and cleaning the multi-source data and establishing data association mapping relationships; a monitoring map reconstruction unit for constructing an optimized distribution network line interval monitoring map based on the fused data, wherein the monitoring map includes basic line information, customer impact analysis information, and auxiliary decision-making information; and a dynamic update unit for updating the display content and decision recommendation results of the monitoring map in real time according to real-time data changes and changes in customer-side information.

[0014] The following are further optimizations and / or improvements to the second technical solution of the above invention: The aforementioned multi-source data acquisition unit can also be used to connect to distribution network dispatching systems, marketing systems, GIS systems, and metering terminals to obtain multi-source data.

[0015] The aforementioned data fusion processing unit may include a data cleaning subunit and an association mapping subunit. The data cleaning subunit is used for standardized cleaning, and the association mapping subunit is used to establish data association mapping relationships.

[0016] The aforementioned monitoring diagram reconstruction unit may include an information integration subunit and a view generation subunit. The information integration subunit is used to integrate basic line information, customer impact analysis information, and auxiliary decision-making information, while the view generation subunit is used to construct a monitoring diagram of the distribution network line bays.

[0017] The aforementioned dynamic update unit may include a data monitoring subunit and a refresh triggering subunit. The data monitoring subunit is used to monitor real-time data changes and changes in customer-side information, while the refresh triggering subunit is used to trigger the refresh of the display content of the monitoring chart and the decision recommendation results.

[0018] This invention effectively solves the information and data problems of existing distribution network dispatching systems through the synergistic effect of methods and devices, significantly improving the operation and maintenance and dispatching level of distribution networks. At the information acquisition level, the data acquisition and multi-source data acquisition units of the device work together to break down data silos, integrate data from multiple systems, covering static line archives, real-time operation, customer-side data, and related system data, providing a comprehensive data foundation for subsequent processing. The data fusion processing steps and corresponding units ensure data accuracy and relevance through standardized cleaning and correlation mapping, avoiding data confusion from affecting decision-making. In the monitoring chart information reconstruction stage, combined with the device's functions, an optimized distribution network line interval monitoring chart containing multiple types of key information is constructed, overcoming the shortcomings of traditional monitoring charts with limited information. Basic line information helps dispatchers understand the status of the lines themselves, customer impact analysis information clarifies the scope and extent of the fault's impact on users, and auxiliary decision-making information provides direct support for fault handling and resource scheduling. The dynamic update function ensures the real-time nature of the monitoring chart information, ensuring that dispatchers obtain the latest data and decision recommendations. This invention eliminates the need for dispatchers to query data across systems, shortening fault assessment time, reducing reliance on manual experience, and improving the accuracy of accident location. It provides data support for emergency repair resource scheduling, avoiding resource waste and accelerating repair progress. It fully considers customer needs, improving the targeting and efficiency of fault handling, shortening power outage time, improving power supply reliability, and enhancing user electricity experience. At the same time, it reduces equipment maintenance difficulty and operation and maintenance costs, reduces user complaints, and provides efficient and comprehensive technical support for distribution network dispatching and operation and maintenance, promoting the development of distribution network management towards intelligence and refinement. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the method for optimizing distribution network line interval monitoring map information according to an embodiment of the present invention.

[0020] Figure 2 This is a schematic diagram of the structure of the distribution network line interval monitoring map information optimization device according to an embodiment of the present invention. Detailed Implementation

[0021] The present invention is not limited to the following embodiments, and the specific implementation can be determined according to the technical solution of the present invention and the actual situation.

[0022] The present invention will be further described below with reference to embodiments: Example 1: As Figure 1 As shown, this embodiment provides a method for optimizing distribution network line bay monitoring map information, including: Step 1: Data Acquisition. This involves acquiring multi-source data for the distribution network lines, including static line profiles, real-time operational data, customer-side data, and data from related systems. Data acquisition comprehensively gathers relevant data for the distribution network lines, preventing incomplete dispatch decisions and laying the foundation for subsequent data processing and monitoring chart construction. This ensures that dispatchers have comprehensive data sources covering multiple dimensions, including the lines themselves, operational status, users, and related systems, providing sufficient data support for subsequent steps.

[0023] Step 2, Data Fusion Processing: Standardize and clean the multi-source data, and establish data association mapping relationships. Standardization cleaning can eliminate the influence of data format differences and abnormal data, ensuring data accuracy. Data association mapping can establish connections between different types of data, making the data form an organic whole. In this way, data quality can be improved, and messy data can be avoided from interfering with decision-making. At the same time, it can make data from different sources interconnected, which is convenient for subsequent integration and utilization.

[0024] Step 3: Monitoring Chart Information Reconstruction: Based on the fused data, an optimized monitoring chart of the distribution network line intervals is constructed. The monitoring chart includes basic line information, customer impact analysis information, and decision support information. The reconstructed monitoring chart centrally presents key information, breaking the limitation of single information in traditional monitoring charts. This allows dispatchers to obtain multiple types of important information in the same view, reducing the time dispatchers spend querying multiple systems, improving information acquisition efficiency, and supporting rapid decision-making.

[0025] Step 4: Dynamic Updates: Based on real-time data changes and customer-side information updates, the monitoring chart display content and decision recommendation results are refreshed in real time. Dynamic updates ensure that the monitoring chart information is synchronized with the actual situation, avoiding decision-making errors due to information lag. This allows dispatchers to keep abreast of the latest status of the distribution network lines, adjust decisions in a timely manner, and improve dispatch response speed.

[0026] In this embodiment, in step one above, the static data of the line includes the line type, wire diameter, tower parameters, and equipment service life; the real-time operating data includes current, voltage, load factor, switch status, and meter readings; the customer-side data includes user level, electricity usage type, contact information, and power outage sensitivity; the associated system data includes fault analysis results from the dispatch system, work order information from the marketing system, and topological relationships from the GIS system. Clearly defining the specific content of each type of data ensures the relevance and completeness of data collection, avoiding the omission of key data items. This allows for more accurate data collection, providing specific and effective data for subsequent data fusion and monitoring map construction, and improving the overall operability of the solution.

[0027] In this embodiment, in step two above, the data association mapping relationship includes the binding relationship between customer-side data and line topology nodes, as well as the spatiotemporal alignment relationship between real-time operational data and static archive data. In step three, the basic line information is the superimposed display information of line static archive data and real-time operational data; the customer impact analysis information includes the level distribution information of users covered by the line and the information on the scope of power outage impact; and the auxiliary decision-making information includes fault repair path planning information and load transfer scheme recommendation information. Clarifying the specific composition of the data association method and various types of information in the monitoring chart can ensure effective data fusion and practical monitoring chart information. This makes the data association more logical, the monitoring chart information more in line with scheduling needs, and improves the accuracy and efficiency of scheduling decisions.

[0028] In this embodiment, in step two above, standardized cleaning includes data format unification, outlier removal, and missing value completion. Clearly defining the specific operations of standardized cleaning can ensure that the data processing process is standardized and improve data quality. This can eliminate the negative impact of data format differences, outlier data, and missing data, ensure data reliability, and provide high-quality data for subsequent steps.

[0029] In this embodiment, step three above includes a hierarchical display setting for basic line information, customer impact analysis information, and auxiliary decision-making information. The hierarchical display can distinguish information according to its importance, making it convenient for dispatchers to quickly focus on key information. This can improve information viewing efficiency, allowing dispatchers to quickly obtain core information in emergency situations and shorten decision-making time.

[0030] During operation, the system first collects multi-source data in step one, covering static line files, real-time operation, customer-side data, and related system data. Next, step two involves data fusion processing, standardizing and cleaning the collected data and establishing correlation mappings. Then, step three reconstructs the monitoring chart information, constructing an optimized distribution network line bay monitoring chart with hierarchical display of multiple types of information based on the fused data. Finally, step four enables dynamic updates, refreshing the monitoring chart content and decision recommendation results according to data changes and customer-side information updates. The overall process is coherent, with each step supporting the others, effectively improving distribution network scheduling efficiency and fault handling capabilities, enhancing power supply reliability, and improving user electricity experience.

[0031] This invention adds the display of physical characteristics of distribution network lines, such as wire diameter, length, and load-bearing capacity, to the distribution network line bay diagram, enabling dispatchers to fully understand the line's operating status and load-bearing capacity. Through data interfaces or data platforms, it achieves data integration between the D5000 system and other systems such as the acquisition system, marketing system, line loss system, and power supply service command system, ensuring dispatchers can obtain comprehensive data support in a timely manner. It links the entire lifecycle data of equipment with the line bay diagram, allowing dispatchers to fully understand the historical and current status of equipment, providing data support for equipment maintenance and management. Through improved data display and system integration, it optimizes the accident handling process, improves accident handling efficiency, shortens power outage time, and enhances power supply reliability. By improving power supply reliability and shortening power outage time, it enhances the user's normal electricity experience and reduces user complaints and dissatisfaction. By strengthening the collection and utilization of customer-side data, such as customer electricity demand and habits, it provides more comprehensive data support for fault handling, improving fault handling speed and user satisfaction. By introducing intelligent operation and maintenance tools, such as fault diagnosis systems and resource scheduling systems, it improves operation and maintenance efficiency and accuracy, and reduces operation and maintenance costs.

[0032] This invention optimizes the monitoring information of distribution network line intervals, which can improve the speed of fault diagnosis and the efficiency of fault handling. Dispatchers can fully understand the nature of the line by relying on a single system, and can adjust the threshold to issue specified alarm information and handling suggestions, thereby improving the efficiency of fault diagnosis and handling, efficiently utilizing emergency repair resources, improving power supply reliability, and bringing a better power experience to users. Each functional module can be displayed independently on a page or combined according to the complexity of the line, realizing the hierarchical presentation of information.

[0033] Example 2: Figure 2As shown, this embodiment provides a distribution network line interval monitoring map information optimization device, including: a multi-source data acquisition unit, used to acquire multi-source data of the distribution network line, wherein the multi-source data includes line static archive data, real-time operation data, customer-side data and related system data; the multi-source data acquisition unit, as a data entry point, can collect data from multiple systems and multiple dimensions, providing a data foundation for subsequent processing by the device, thereby ensuring that the data acquired by the device is comprehensive and meets the needs of subsequent data fusion and monitoring map construction.

[0034] The data fusion processing unit is used to standardize and clean multi-source data and establish data association mapping relationships. The data fusion processing unit can process the collected messy data, improve data quality and establish relationships between data. In this way, scattered data can be transformed into ordered and related usable data, providing high-quality data support for monitoring chart reconstruction.

[0035] The monitoring map reconstruction unit is used to construct an optimized monitoring map of the distribution network line intervals based on the fused data. The monitoring map includes basic line information, customer impact analysis information, and auxiliary decision-making information. The monitoring map reconstruction unit can transform the fused data into a visual monitoring map, centrally presenting key information. This allows dispatchers to intuitively obtain multiple types of important information, reduce information query time, and improve decision-making efficiency.

[0036] The dynamic update unit is used to refresh the display content and decision recommendation results of the monitoring chart in real time based on changes in real-time data and customer-side information. The dynamic update unit can ensure the real-time information of the monitoring chart and avoid information lag. In this way, dispatchers can keep abreast of the latest status of the distribution network, adjust decisions in a timely manner, and improve the practicality and response speed of the device.

[0037] In this embodiment, the aforementioned multi-source data acquisition unit is also used to connect with the distribution network dispatch system, marketing system, GIS system, and metering terminal to obtain multi-source data. Clearly defining the connection objects of the multi-source data acquisition unit can ensure that the data acquisition channels are clear, improve the stability and reliability of data acquisition, and make data acquisition more secure, avoiding data loss or acquisition failure due to connection problems.

[0038] In this embodiment, the data fusion processing unit includes a data cleaning subunit and an association mapping subunit. The data cleaning subunit is used for standardized cleaning, and the association mapping subunit is used to establish data association mapping relationships. By splitting the data fusion processing unit into two subunits, functional subdivision can be achieved, improving the professionalism and efficiency of each step. In this way, data cleaning and association mapping can be performed efficiently, further improving the quality and speed of data processing.

[0039] In this embodiment, the aforementioned monitoring diagram reconstruction unit includes an information integration subunit and a view generation subunit. The information integration subunit is used to integrate basic line information, customer impact analysis information, and auxiliary decision-making information, while the view generation subunit is used to construct a monitoring diagram of the distribution network line intervals. By splitting the monitoring diagram reconstruction unit into two subunits, information integration and view generation can be realized separately, improving the orderliness and quality of monitoring diagram construction. This ensures that the integrated information is comprehensive and logically clear, and that the generated monitoring diagram meets scheduling requirements and is easy to view and use.

[0040] In this embodiment, the dynamic update unit includes a data monitoring subunit and a refresh triggering subunit. The data monitoring subunit is used to monitor real-time data changes and changes in customer-side information, while the refresh triggering subunit is used to trigger the refresh of the display content of the monitoring chart and the decision recommendation results. By splitting the dynamic update unit into two subunits, data monitoring and refresh triggering can be realized separately, improving the timeliness and accuracy of dynamic updates. This ensures that data changes are detected in a timely manner and refreshes are triggered quickly, guaranteeing the real-time information of the monitoring chart.

[0041] During operation, the multi-source data acquisition unit connects with various systems and terminals to acquire multi-source data and transmits it to the data fusion and processing unit. The data cleaning subunit standardizes and cleans the data, and the association mapping subunit establishes data association mappings. The processed data is then transmitted to the monitoring chart reconstruction unit, where the information integration subunit merges various types of information, and the view generation subunit constructs an optimized monitoring chart of the distribution network line intervals. Simultaneously, the data monitoring subunit monitors data changes and customer-side information changes. Once a change is detected, the refresh trigger subunit triggers an update of the monitoring chart content and decision recommendation results. All units and subunits work collaboratively to optimize the information in the distribution network line interval monitoring chart, providing efficient support for distribution network dispatching and improving fault handling efficiency and power supply reliability.

[0042] In existing technologies, the distribution network line bay monitoring diagram includes the following functional modules: Substation primary wiring diagram module: Understand the substation wiring method and monitor the status of primary equipment on this line; Telemetry information module: Monitors line voltage, current, active power, and reactive power information; In-station handle position module: Monitors the position status of handles, enabling remote control operation and local manual operation; Protection function pressure plate module: Monitors the status of line function pressure plates; Communication signal module diagram: Monitors the communication status of this line; Protection module: Monitors the current protection configuration and operation status of the line.

[0043] Through this invention, the following functional modules are added to the power distribution network line bay monitoring diagram: The static information module for power lines includes: line length, line type (cable, overhead), service life, line current carrying capacity (winter, summer), maintenance unit (county company, work team), and equipment responsible person (maintenance personnel). Most of this data is static and requires no maintenance, allowing for immediate access to information about the line type and maintenance unit. The static database architecture results in infrequent data updates and supports quick access to basic line records, reducing information retrieval time.

[0044] Customer Nature Module: Whether this line connects to important user lines, number of important users, important user level, user details, capacity, current operation of important users, whether this line is the main power supply line, whether there is a backup power supply, whether there is a low-voltage automatic transfer switch, operating status of important user meters (data source: acquisition system and marketing system), important user level, user details, capacity, current operation of important users, whether this line is the main power supply line, whether there are industrial users, mainly reflecting the customer nature. This module allows for immediate understanding of the operating status and impact scope of important, sensitive, industrial, and commercial users in case of faults. Some data in this module is maintained regularly to ensure the timeliness of some information.

[0045] Customer Information Module: This module displays the current operating status of the line, including the total number of high- and low-voltage users and the number of users with normal electricity consumption (based on the data collection and marketing system's user meter status; preset values ​​can be used to assess low-voltage faults and some line breakages). The data in this module is dynamic, derived from the data collection system and the marketing system's customer meter operating status, enabling accurate assessment of the number of users affected by a fault trip.

[0046] The transformer area information and user distribution module includes: the number of residential communities and buildings connected to this line, community type (whether it is an elevator building, whether it is a high-density community, whether there are people receiving oxygen therapy), number of transformer areas, transformer area operation status, customer (transformer area) manager information and contact person, operation and maintenance team (team leader information and contact person). After a failure in this module, the scope of the failure can be correctly determined, whether there is any social public opinion situation, whether there is any life-threatening situation, and relevant marketing teams can be notified to improve customer satisfaction and effectively control the occurrence of negative public opinion. Most of the data in this module comes from the marketing collection system, so the timeliness of the data must be guaranteed and regular maintenance is required.

[0047] Line Connection Module: Clicking this module will display the single-line diagram and connection relationships of this line. The status information of the circuit breakers in the distribution network of this line can be set in this module. After a fault, the connection relationships of this line can be understood immediately, and relevant reverse connection plans can be prepared. This module can be used to process complex distribution network lines (currently, the dispatch system only has the substation connection diagram, and the substation line connection relationships are complex. Exiting and re-entering requires searching for this line again, which is time-consuming). It effectively improves the speed of analysis and the efficiency of fault handling, shortens the power outage time, and improves the reliability of power supply.

[0048] Emergency Response Plan Module: This module includes pre-set emergency response plans for important users on this line, precautions for handling faults according to the nature of the line, tripping response plans, and reverse-current response plans for faults that cannot be isolated. It also pre-sets possible faults and multiple reverse-current solutions. This module mainly improves fault handling efficiency, reduces power outage time, and enhances power supply reliability.

[0049] Fault Trip Statistics Module: This module compiles historical trip records for this line, including the location of related faults, handling methods, the time of the most recent trip, the number of trips this year, and the planned outage time. This module can provide information on the line's historical trip records and the number of outages, and can be used as a reference for handling complex lines in this fault case.

[0050] Each of the above functional modules can be set as a separate page or multiple modules on one page, depending on the complexity of the line. Before optimization, dispatchers often needed to rely on multiple systems to obtain information such as line parameters, properties, and impact range when handling distribution network faults. This cross-system query method was not only time-consuming but also prone to errors, resulting in low fault handling efficiency, prolonged power outage time, reduced power supply reliability, and impact on users' normal power experience. This invention optimizes the distribution network line bay diagram, allowing dispatchers to understand all line parameters, properties, and impact range information using only a single system. Specifically: Quickly obtain line information: Dispatchers can quickly obtain static information (such as line length, nature, service life, etc.) and dynamic information (such as customer nature, customer information, transformer area information, etc.) of the line through the interval diagram without having to query across systems.

[0051] Quickly determine the location and scope of the fault: Based on the comprehensive information provided by the interval diagram, the dispatcher can quickly determine the location and scope of the fault, providing an accurate basis for fault handling.

[0052] Timely early warning: Based on the analysis results, dispatchers can issue early warnings to relevant work teams in a timely manner to ensure the timely dispatch of repair resources and the rapid handling of faults.

[0053] Effectively soothe customer emotions: Timely warnings and fault handling can effectively soothe customer emotions and reduce user dissatisfaction and complaints.

[0054] Improved handling efficiency: The optimization of the interval diagram makes the fault handling process smoother, improves handling efficiency, and shortens power outage time.

[0055] Improved power supply reliability: Power supply reliability has been significantly improved by shortening outage time and increasing response efficiency.

[0056] Improving the user's electricity experience: Increased power supply reliability and a more reassuring user experience effectively enhance the user's electricity usage experience.

[0057] Reduce complaints and negative public opinion: Through timely fault handling and effective customer reassurance, the probability of complaints and negative public opinion has been reduced.

[0058] This invention forms a complete solution from data integration to service optimization through a chain of technological innovations: data fusion-driven (system architecture) → rapid diagnosis and localization (core function) → visual decision-making (auxiliary tool) → efficiency improvement (result verification). By integrating multiple system data sources, this invention achieves a single, efficient fault handling channel, avoiding complex processes and repetitive data retrieval; it enables rapid fault diagnosis and real-time early warning based on a single system, improving response efficiency; it combines protection action signals, meter disconnection events, and transformer area power outage status to achieve precise fault location; it correlates customer importance-level data to dynamically calculate the fault impact range and assist in resource priority allocation; dynamic topology coloring technology intuitively displays the power grid status, and combined with emergency repair path planning algorithms, it provides optimal route suggestions; it improves emergency repair resource utilization and shortens power outage time through accurate data support; it reduces power outage duration and improves power supply reliability indicators through rapid handling; it monitors user power consumption status in real time, promptly soothes user emotions, and prevents the spread of negative public opinion; it shortens the fault handling cycle, reduces user complaint rates, and improves the quality of power supply services.

[0059] It should be noted that, in this invention, "distribution network line interval monitoring chart" refers to a visual view used to display information related to distribution network line intervals, allowing dispatchers to monitor and analyze the line operation status; "multi-source data" refers to a collection of data related to distribution network lines from different systems and dimensions, including data on the lines themselves, their operation status, users, and related systems; "data association mapping relationship" refers to establishing corresponding relationships between different types of data through specific rules, enabling scattered data to form an organic whole; "standardized cleaning" refers to the operation of unifying the format of multi-source data, removing abnormal data, and completing missing data to improve data quality; and "dynamic update" refers to the process of timely updating the monitoring chart content and decision recommendation results based on real-time data changes and changes in customer-side information to ensure the timeliness of information.

[0060] The above technical features constitute the embodiments of the present invention, which have strong adaptability and implementation effect. Unnecessary technical features can be added or removed according to actual needs to meet the needs of different situations.

Claims

1. A method for optimizing monitoring map information of distribution network line intervals, characterized in that, include: Step 1: Data Acquisition: Obtain multi-source data for the distribution network lines, including static line profile data, real-time operational data, customer-side data, and related system data. Step 2, Data Fusion Processing: Standardize and clean the multi-source data, and establish data association mapping relationships; Step 3: Reconstruction of monitoring map information: Based on the fused data, construct an optimized monitoring map of the distribution network line bays. The monitoring map includes basic line information, customer impact analysis information, and decision support information. Step 4: Dynamic Updates: Based on real-time data changes and client-side information updates, refresh the monitoring chart's display content and decision recommendation results in real time.

2. The method for optimizing distribution network line bay monitoring map information according to claim 1, characterized in that, In step one, the static data of the line includes the line type, wire diameter, tower parameters and equipment service life; the real-time operation data includes current, voltage, load factor, switch status and meter readings; the customer-side data includes user level, electricity usage type, contact information and power outage sensitivity. The associated system data includes fault assessment results from the scheduling system, work order information from the marketing system, and topological relationships from the GIS system.

3. The method for optimizing distribution network line bay monitoring map information according to claim 1 or 2, characterized in that, In step two, the data association mapping relationship includes the binding relationship between customer-side data and line topology nodes, as well as the spatiotemporal alignment relationship between real-time operation data and static archive data. In step three, the basic line information is the superimposed display information of line static archive data and real-time operation data, the customer impact analysis information includes the level distribution information of users covered by the line and the information on the scope of power outage impact, and the auxiliary decision-making information includes fault repair path planning information and load transfer scheme recommendation information.

4. The method for optimizing distribution network line bay monitoring map information according to claim 1 or 2, characterized in that, In step two, standardized cleaning includes standardizing data formats, removing outliers, and filling in missing values.

5. The method for optimizing distribution network line bay monitoring map information according to claim 1 or 2, characterized in that, In step three, the monitoring chart information reconstruction also includes the hierarchical display settings for basic line information, customer impact analysis information, and auxiliary decision-making information.

6. A device for optimizing monitoring map information of distribution network line bays, characterized in that, include: The multi-source data acquisition unit is used to acquire multi-source data of the distribution network lines, including static file data of the lines, real-time operation data, customer-side data and related system data. The data fusion processing unit is used to standardize and clean multi-source data and establish data association mapping relationships; The monitoring map reconstruction unit is used to construct an optimized monitoring map of the distribution network line bays based on the fused data. The monitoring map includes basic line information, customer impact analysis information, and auxiliary decision-making information. The dynamic update unit is used to refresh the display content of the monitoring chart and the decision recommendation results in real time based on changes in real-time data and customer-side information.

7. The distribution network line bay monitoring map information optimization device according to claim 6, characterized in that, The multi-source data acquisition unit is also used to connect to the power distribution network dispatching system, marketing system, GIS system and metering terminal to obtain multi-source data.

8. The distribution network line bay monitoring map information optimization device according to claim 6 or 7, characterized in that, The data fusion processing unit includes a data cleaning subunit and an association mapping subunit. The data cleaning subunit is used for standardized cleaning, and the association mapping subunit is used to establish data association mapping relationships.

9. The distribution network line bay monitoring map information optimization device according to claim 6 or 7, characterized in that, The monitoring diagram reconstruction unit includes an information integration subunit and a view generation subunit. The information integration subunit is used to integrate basic line information, customer impact analysis information, and auxiliary decision-making information, while the view generation subunit is used to construct a monitoring diagram of the distribution network line bays.

10. The distribution network line bay monitoring map information optimization device according to claim 6 or 7, characterized in that, The dynamic update unit includes a data monitoring subunit and a refresh triggering subunit. The data monitoring subunit is used to monitor real-time data changes and changes in customer-side information, while the refresh triggering subunit is used to trigger the refresh of the display content of the monitoring chart and the decision recommendation results.

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