Power failure analysis and early warning system based on one graph of power grid

Abstract

According to the power failure analysis and early warning system based on the power grid graph, through effective combination of the acquisition module and the power failure analysis and early warning platform, power failure events are monitored in real time, intelligent analysis and early warning are carried out, power failure information is visually displayed, and power grid operation personnel are helped to rapidly master power failure conditions and make accurate decisions and responses; the scheme comprises an acquisition unit for acquiring fault detection data of a power grid measurement center and a power grid marketing system in real time, and importing the fault detection data to a database of a power failure analysis early warning platform; the power failure analysis and early warning platform is used for carrying out data preprocessing, data analysis, telemetering data dynamic threshold adjustment and early warning on the fault detection data of the database; the power failure analysis early warning platform comprises a fault power failure unit, a fault work order unit, a power grid graph alarm display unit and an event message queue alarm unit.

Description

Technical Field

[0001] The present invention relates to the technical field of power outage analysis, and in particular to a power outage analysis and early warning system based on a power grid map and a monitoring system thereof. Background Art

[0002] With the improvement of living standards, users have higher and higher requirements for power supply reliability. Frequent power outages will seriously affect residents' lives and business operations. Building an early warning system can effectively reduce unplanned power outages and improve user experience. With the growth of electricity demand, traditional power grids face many challenges such as management complexity, stability and efficiency. By introducing data communication, sensing and control technologies, smart grids can monitor, manage and optimize power flow in real time, and the application of technologies such as deep learning provides powerful analysis and decision support for smart grids.

[0003] The development of new power systems has made data more heterogeneous and complex, bringing new challenges to the integration and analysis of power system big data. The data island phenomenon is serious. The data in the distribution network comes from multiple different systems and data sources, such as measurement centers, marketing systems, SCADA (supervisory control and data acquisition) systems, GIS (geographic information systems), DMS (distribution management systems), etc. There is a lack of unified integration and sharing mechanisms between these data, resulting in information islands and difficulty in forming a global perspective.

[0004] In the current power grid operation, the power grid measurement center and marketing system collect a large amount of power outage data through their respective terminal systems. However, the integration of these data mainly relies on manual work, which is not only time-consuming and labor-intensive, but also inefficient. Considering that power outages of distribution network users directly affect the power consumption experience of end users, the alarm and processing of power outage events are extremely important. Therefore, for the monitored power outage data, it is necessary to realize the first-time alarm so as to quickly respond to and handle the power outage event.

[0005] In addition, in order to more fully understand the scope and extent of the power outage, it is necessary to visualize and analyze the power outage information in the monitoring area. This includes viewing the overall distribution and number of power outages in the entire network, as well as the specific statistical information of substations, lines, transformers, users, and communities affected. This information is crucial for formulating effective power outage response strategies and optimizing power grid operation and maintenance plans.

[0006] However, there is currently a lack of a power outage analysis and management system specifically for distribution networks that can achieve the above functions. Such a system should be able to automatically integrate power outage data from different data sources, monitor power outage events in real time, and perform intelligent analysis and early warning. The power outage information is displayed through a visual interface to help power grid operators quickly grasp the power outage status and make accurate decisions and responses. Through in-depth analysis of power outage data, the weak links of the power grid can be identified, providing a scientific basis for power grid planning, construction and transformation, optimizing resource allocation, and improving overall efficiency. The ability to quickly and accurately collect power outage information and provide early warnings is crucial to quickly launching emergency plans and ensuring the power supply of key facilities.

[0007] In the face of the above challenges, the power industry is accelerating its transformation towards digitalization and intelligence, aiming to improve operational efficiency and service quality through advanced information technology. Among them, building a power outage analysis and early warning system based on "one map of the power grid" is a key link. The system aims to achieve comprehensive integration, intelligent processing and visual display of data, providing strong support for the lean management of the distribution network.

[0008] In summary, the development of a power outage analysis and early warning system based on "one map of the power grid" is an inevitable choice to cope with the current distribution network management challenges, meet the needs of digital transformation, and improve user satisfaction and social influence. By integrating multi-source data, applying intelligent algorithms, and realizing real-time monitoring and early warning, the system will provide a solid technical guarantee for the efficient, safe, and reliable operation of the distribution network. Summary of the invention

[0009] The present invention aims to address the technical defects of the prior art and provide a power outage analysis and early warning system based on a power grid map. Through the effective combination of the acquisition module and the power outage analysis and early warning platform, the system can monitor power outage events in real time, conduct intelligent analysis and early warning, and visualize the power outage information, so as to help power grid operators quickly grasp the power outage status and make accurate decisions and responses.

[0010] The present invention provides the following technical solutions: a power outage analysis and early warning system based on a power grid map, including an acquisition unit, which acquires fault detection data from a power grid measurement center and a power grid marketing system in real time, and imports the fault detection data into a database of a power outage analysis and early warning platform; the power outage analysis and early warning platform performs data preprocessing, data analysis, and dynamic adjustment of thresholds and early warnings on the fault detection data in the database of telemetry data;

[0011] The power outage analysis and early warning platform includes a fault power outage unit, a fault work order unit, a power grid one-picture alarm display unit, and an event message queue alarm unit;

[0012] A fault power outage unit is used to display the power outage information in the monitoring area by category; the fault power outage unit includes cumulative power outage events, main line power outage, branch line power outage, distribution transformer power outage, affected cells, power outage users, sensitive users, and power restoration rate;

[0013] A fault work order unit is used to display the power outage fault work orders in the monitoring area; the fault work order unit includes a unit bar chart display and a type bar chart display;

[0014] A grid one-picture alarm display unit displays the power outage situation in the monitoring area based on a grid one-picture; the power outage situation includes power outage in process, power outage repaired, work order in process, work order repaired, and emergency repair station;

[0015] The event message queue alarm unit is used to display the power outage events in the monitoring area in a carousel and send SMS and email notifications of power outage events.

[0016] Preferably, the acquisition unit simultaneously acquires fault detection data from the power grid measurement center and the power grid marketing system through the SpringBoot framework structure and the kafka message queue.

[0017] Preferably, the power outage analysis and warning platform adopts a high-speed data transmission protocol and a distributed processing architecture.

[0018] Preferably, the telemetry data dynamically adjusts the threshold using a machine learning neural network regression model.

[0019] Preferably, the power outage analysis and early warning platform performs equipment analysis on stations, lines, and transformers in the monitoring area according to the equipment topology relationship, realizes distribution and quantity statistics through the geographical location positioning of the equipment ledger location information on a power grid map, collects social-level community lists and geographical location information, matches user information according to the geographical scope, matches the relationship between equipment and communities and users according to the household-transformer relationship, and matches the distribution and quantity statistics of the affected communities and users on a power grid map according to the actual geographical location of the power outage event.

[0020] Preferably, the accumulated power outage events can be queried, reset, and the corresponding accumulated power outage event list can be exported according to the unit, power outage type, and power outage status. The accumulated power outage event list includes status, fault number, line name, unit name, type, power outage start time, and power outage end time.

[0021] Preferably, the affected cell includes serial number, status, cell name, power outage start time, power outage end time, cell address, contact person, and contact information.

[0022] Preferably, the power outage users include high-voltage users who have power supplied and not supplied, low-voltage users who have power supplied and not supplied, low-voltage non-residential users who have power supplied and not supplied, and sensitive users who have power supplied and not supplied, and a list of power outage users can be exported. The list of power outage users includes serial number, account number, account name, electricity usage address, sensitive users, user classification, industry classification, electricity usage category, power outage start time, and power outage end time.

[0023] Preferably, the sensitive user includes serial number, user information, and user steward information. The user information includes user number, user name, electricity address, contact information, backup number, user tag, and user sensitivity. The user steward information includes name, contact information, and position.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] The present invention discloses a power outage analysis and early warning system based on a power grid map. It is a comprehensive solution that aims to provide comprehensive power outage monitoring, analysis and early warning capabilities for power grid operators through real-time data collection, data analysis and intuitive visual display. The system includes an acquisition unit, which is responsible for real-time acquisition of fault detection data from the power grid measurement center and the power grid marketing system. After preliminary cleaning and formatting, the collected data is imported into the database of the power outage analysis and early warning platform, providing a basis for subsequent analysis and early warning. These data are the basis for subsequent processing by the power outage analysis and early warning platform; the power outage analysis and early warning platform performs data preprocessing, data analysis, dynamic adjustment of thresholds and early warnings on the fault detection data in the database by telemetry data;

[0026] 1. Fault power outage unit

[0027] This unit classifies the power outage information in the monitoring area according to different dimensions, such as cumulative power outage events, main line power outage (main line power outage), branch line power outage (branch line power outage), distribution transformer power outage (distribution transformer power outage), affected communities, power outage users, sensitive users (such as key facilities such as hospitals and schools), and power restoration rate, etc., to help operators quickly identify the scope, impact and priority of the power outage, and provide a basis for formulating emergency repair plans;

[0028] 2. Fault work order unit

[0029] The power outage fault work orders are displayed in two ways: unit bar chart and type bar chart. The unit bar chart displays the number of work orders by responsible unit or area, while the type bar chart displays them by fault type (such as equipment failure, external force damage, etc.), which makes it easier for operators to understand the fault distribution, responsibility and fault type, and promotes the rational allocation of resources and rapid fault handling;

[0030] 3. One-picture grid alarm display unit

[0031] Based on a grid map, using geographic information system (GIS) technology, the physical structure, equipment location and real-time status of the grid are integrated into a single map. The grid map dynamically displays information such as power outage in process, power outage repaired, work order in process, work order repaired, and emergency repair station. The grid operation status and emergency repair progress are intuitively and visually displayed, improving emergency response speed and decision-making efficiency.

[0032] 4. Event message queue alarm unit

[0033] Carousel display: Through rolling playback, power outage events in the monitoring area are displayed in real time to ensure that operators will not miss any important information;

[0034] Notification mechanism: For critical power outage events, the system automatically triggers notification methods such as SMS and email to send early warning information to relevant personnel to ensure immediate communication of information;

[0035] In summary, the power outage analysis and early warning system based on a power grid map provides a powerful tool for power grid operators to quickly respond to power outage events through real-time data acquisition, intelligent analysis and visual display. This not only greatly improves the power grid operators' ability to quickly perceive and respond to power outages and reduce power outage time, but also helps to optimize resource allocation, reduce the impact of power outages on users, and improve the safety and reliability of power grid operation. In addition, the flexibility and scalability of the system also provide a solid foundation for future smart grid upgrades and business expansion. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a schematic diagram of the main interface of the power outage analysis and early warning platform of the present invention;

[0037] Figure 2 This is a schematic diagram of the second main interface of the power outage analysis and early warning platform of the present invention;

[0038] Figure 3 This is a schematic diagram of the interface for accumulating power outage events on the power outage analysis and early warning platform of the present invention;

[0039] Figure 4 This is a schematic diagram of a power outage user interface of a power outage analysis and early warning platform of the present invention;

[0040] Figure 5 This is a schematic diagram of a sensitive user interface of a power outage analysis and early warning platform of the present invention;

[0041] Figure 6 This is a schematic diagram of the interface of the community affected by the power outage analysis and early warning platform of the present invention. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. All other embodiments obtained by ordinary technicians in the field without making creative work based on the embodiments of the present invention shall fall within the scope of protection of the present invention.

[0043] The monitoring and analysis technology mentioned in the present invention, especially in the application of low-oil equipment, does have wide applicability and potential. This technology is not only limited to the monitoring of low-oil equipment, but can also be extended to other types of monitoring data analysis.

[0044] like Figures 1 to 6 As shown, it shows a specific embodiment of the present invention: Figures 1 to 6 As shown, the power outage analysis and early warning system based on a power grid one-picture disclosed by the present invention includes an acquisition unit, which acquires fault detection data of a power grid measurement center and a power grid marketing system in real time, and imports the fault detection data into a database of a power outage analysis and early warning platform; the power outage analysis and early warning platform performs data preprocessing, data analysis, and telemetry data dynamic adjustment threshold and early warning on the fault detection data in the database;

[0045] The power outage analysis and early warning platform includes a fault power outage unit, a fault work order unit, a power grid one-picture alarm display unit, and an event message queue alarm unit;

[0046] A fault power outage unit is used to display the power outage information in the monitoring area by category; the fault power outage unit includes cumulative power outage events, main line power outage, branch line power outage, distribution transformer power outage, affected cells, power outage users, sensitive users, and power restoration rate;

[0047] A fault work order unit is used to display the power outage fault work orders in the monitoring area; the fault work order unit includes a unit bar chart display and a type bar chart display;

[0048] A grid one-picture alarm display unit displays the power outage situation in the monitoring area based on a grid one-picture; the power outage situation includes power outage in process, power outage repaired, work order in process, work order repaired, and emergency repair station;

[0049] The event message queue alarm unit is used to display the power outage events in the monitoring area in a carousel and send SMS and email notifications of power outage events.

[0050] Preferably, the acquisition unit simultaneously acquires fault detection data from the power grid measurement center and the power grid marketing system through the SpringBoot framework structure and the kafka message queue.

[0051] The process in which the acquisition unit simultaneously acquires fault detection data from the power grid measurement center and the power grid marketing system through the SpringBoot framework structure and the Kafka message queue is an efficient and reliable data integration solution.

[0052] 1. The role of SpringBoot framework structure

[0053] The SpringBoot framework provides a simple integration method that allows developers to easily integrate external components such as Kafka into applications. In the SpringBoot project, by adding corresponding dependencies and configurations, you can connect to and use the Kafka message queue.

[0054] By using SpringBoot's RESTful API or database access capabilities, fault detection data can be obtained from the power grid measurement center and power grid marketing system. The acquired data can be pre-processed, such as data cleaning and format conversion, to meet the needs of subsequent analysis.

[0055] 2. The role of Kafka message queue

[0056] As a high-performance distributed message queue system, Kafka can receive fault detection data from the power grid measurement center and the power grid marketing system in real time. Data is transmitted in Kafka in the form of messages and stored in a specified topic for subsequent consumer processing.

[0057] The introduction of Kafka achieves the decoupling between data producers and consumers, allowing data acquisition and processing to be performed independently, improving the scalability and flexibility of the system. When the data format or interface of the power grid measurement center and the power grid marketing system changes, only the Kafka producer code needs to be adjusted without modifying the logic on the consumer side.

[0058] Kafka supports persistent storage of messages. Even if the power grid measurement center and power grid marketing system fail, the sent data will not be lost. By configuring Kafka's replication mechanism and ISR (In-Sync Replicas) strategy, the reliability and consistency of data can be ensured.

[0059] 3. Startup and testing

[0060] Start the SpringBoot application to ensure that the Kafka producer and consumer can work properly. Test the receiving and processing capabilities of the Kafka message queue by simulating the data transmission of the power grid measurement center and the power grid marketing system.

[0061] In summary, the combination of SpringBoot framework and Kafka message queue can efficiently achieve the goal of obtaining fault detection data from the power grid measurement center and power grid marketing system. This solution not only improves the real-time and reliability of data, but also enhances the scalability and flexibility of the system.

[0062] Comprehensive integration of various scenarios. By accessing data from multiple systems and conducting comprehensive integration, data integrity is guaranteed to the greatest extent possible. This enables comprehensive and accurate basis for decision-making, thereby improving the scientificity and effectiveness of decision-making.

[0063] Preferably, the power outage analysis and warning platform adopts a high-speed data transmission protocol and a distributed processing architecture.

[0064] The power outage analysis and early warning platform adopts a high-speed data transmission protocol and a distributed processing architecture to ensure that the platform can process and analyze fault detection data from the power grid measurement center and the power grid marketing system in real time and efficiently.

[0065] 1. High-speed data transmission protocol

[0066] High-speed data transmission protocols are key to ensuring fast and accurate data transmission between power grid measurement centers, power grid marketing systems, and power outage analysis and early warning platforms. These protocols usually follow the data transmission standards of power system real-time dynamic monitoring systems, such as "Power System Real-time Dynamic Monitoring System Part 2: Data Transmission Protocol". These standards specify the format, rate, and reliability requirements for real-time data transmission to ensure data integrity and timeliness.

[0067] In the power outage analysis and early warning platform, the application of high-speed data transmission protocol is mainly reflected in the following aspects:

[0068] Real-time: Through high-speed data transmission protocols, the platform can obtain fault detection data from the power grid measurement center and power grid marketing system in real time to ensure the timeliness of the data.

[0069] Reliability: High-speed data transmission protocols usually have data verification and retransmission mechanisms to ensure the integrity and accuracy of data during transmission.

[0070] Scalability: As the scale of the power grid expands and the amount of data increases, high-speed data transmission protocols can support higher data transmission rates and larger data volumes to meet the needs of future power grid development.

[0071] 2. Distributed processing architecture

[0072] The distributed processing architecture is the core of the power outage analysis and early warning platform to process and analyze a large amount of fault detection data. This architecture distributes computing tasks and data to multiple nodes to achieve parallel processing and load balancing, thereby improving the system's processing capacity and response speed.

[0073] In the power outage analysis and warning platform, the application of distributed processing architecture is mainly reflected in the following aspects:

[0074] Parallel processing: Distributed processing architecture can split complex computing tasks into multiple subtasks and execute them in parallel on multiple nodes. This can significantly improve the speed and efficiency of data processing.

[0075] Load balancing: Through the distributed processing architecture, the platform can dynamically allocate tasks according to the load conditions of the nodes, ensuring load balancing of each node and avoiding single point overload.

[0076] High availability and fault tolerance: Distributed processing architectures usually have fault detection and recovery mechanisms. When a node fails, tasks can be automatically transferred to other nodes for continued execution, ensuring the continuous operation of the system and the integrity of the data.

[0077] In terms of specific implementation, the power outage analysis and early warning platform can adopt a distributed architecture based on microservices, split different functional modules into independent microservices, and achieve high availability and elastic scaling of services through mechanisms such as service registration and discovery, load balancing, and fuses. In addition, technologies such as distributed databases and distributed caches can also be used to improve the efficiency of data access and processing.

[0078] In summary, high-speed data transmission protocols and distributed processing architecture are key technologies for the power outage analysis and early warning platform to achieve real-time and efficient data processing and analysis. The application of these technologies not only improves the processing capacity and response speed of the platform, but also enhances the scalability and reliability of the system, providing a strong guarantee for the safe and stable operation of the power grid.

[0079] Preferably, the telemetry data dynamically adjusts the threshold using a machine learning neural network regression model.

[0080] The following steps are involved:

[0081] (1) obtaining a normal operating data training model and obtaining a threshold value, wherein the threshold value is used to distinguish between normal operating data and potential fault data;

[0082] (2) Anomaly detection algorithms are used to detect abnormal conditions in equipment operation and determine whether an abnormality exists by comparing the difference between actual data and expected data;

[0083] (3) Rule-based warning thresholds: Based on the data range, change rate, and trend of normal equipment operation, formulate alarm rules and determine the warning threshold when equipment failure occurs;

[0084] (4) simulating equipment operation failures and collecting failure data, wherein the failure data is used to train warning thresholds and to verify and adjust the thresholds during the training process;

[0085] (5) Iterative optimization: Determine the preliminary warning threshold, apply it to the actual monitoring operation of the device, and iteratively optimize and adjust the threshold based on the uploaded actual monitoring data.

[0086] Preferably, Figures 1 to 6 As shown, the power outage analysis and early warning platform performs equipment analysis on stations, lines, and transformers in the monitoring area according to the equipment topology relationship, realizes distribution and quantity statistics through the geographical location positioning of the equipment ledger location information on a power grid map, collects the community list and geographical location information at the social level, matches user information according to the geographical scope, matches the relationship between equipment and communities and users according to the household-transformer relationship, and matches the affected communities and users on a power grid map according to the actual geographical location of the power outage event. Location distribution and quantity statistics.

[0087] The workflow and technical implementation of the power outage analysis and early warning platform are mainly based on multi-dimensional data such as equipment topology relationships, equipment inventory location information, social-level community lists and geographic location information, household change relationships, and the actual geographic location of power outage events.

[0088] 1. Equipment Analysis

[0089] Equipment topology relationship: The power outage analysis and early warning platform first considers the entire power grid as a topology diagram composed of lines and points based on the connection relationship of power grid equipment. This topology analysis can clearly show the connection and dependency relationship between various devices in the power grid. The equipment topology relationship is the existing topology relationship diagram provided in the internal system of the power grid. Through topology analysis, the platform can monitor the status of key equipment such as stations, lines, and transformers in the power grid in real time and discover potential fault points in time.

[0090] 2. Equipment inventory location information

[0091] The equipment inventory location information is the existing information provided by the internal system of the power grid. The platform uses the location information in the equipment inventory to locate each device on a map of the power grid. In this way, the operation and maintenance personnel can intuitively see the distribution of each device in the power grid. Through the equipment inventory location information, the platform can also count the number of devices to help the operation and maintenance personnel understand the total number, type and distribution of devices in the power grid.

[0092] 3. User information matching

[0093] Collect the list of communities and geographic location information at the social level. Utilize the existing information within the power grid, namely the list of communities at the social level. By collecting the list of communities at the social level, the platform obtains basic information such as the name, address, and range of each community. At the same time, the platform also collects the geographic location information of these communities, including longitude and latitude coordinates, so as to accurately locate them on a map of the power grid.

[0094] 4. Household change relationship matching

[0095] The household-transformer relationship refers to the correspondence between power users and transformers. By obtaining household-transformer relationship data (provided by internal data of the power grid), the platform can understand which transformer each user is powered by.

[0096] In power outage analysis and early warning, the matching of household-to-cell relationships is crucial. By matching the relationships between devices, communities, and users, the platform can accurately locate the user groups affected by the power outage.

[0097] 5. Power outage impact analysis

[0098] Power outage event actual geographic location matching

[0099] When a power outage occurs, the platform will accurately locate the power outage on a grid map based on the actual geographic location of the power outage. By comparing the geographic location of the power outage with the topological relationship of the grid equipment, the platform can quickly determine the equipment and areas affected by the power outage.

[0100] 6. Impact on the distribution and quantity of cells and user locations

[0101] After determining the equipment and areas affected by the power outage, the platform will further analyze the communities and users affected by the power outage based on the household-to-transformer relationship data. The platform will locate the communities affected by the power outage and display their distribution on a power grid map. At the same time, the platform will also count the number of users affected by the power outage so that operation and maintenance personnel can understand the scope of the power outage.

[0102] 7. Practical application and effects

[0103] Improve fault location speed: By combining the device topology relationship and device inventory location information, the platform can quickly locate the fault point and improve the efficiency of fault handling.

[0104] Enhanced user service experience: The platform can accurately locate user groups affected by power outages and promptly notify them of power outage information, reducing user complaints and complaints.

[0105] Optimize the allocation of operation and maintenance resources: Through power outage impact analysis, the platform can reasonably allocate operation and maintenance resources to ensure that power supply can be restored to areas affected by the power outage as soon as possible.

[0106] In summary, the power outage analysis and early warning platform achieves real-time monitoring and fault early warning of stations, lines, transformers and other equipment in the power grid through the integration and analysis of multi-dimensional data. At the same time, the platform can also accurately locate the user groups affected by the power outage and optimize the configuration of operation and maintenance resources, providing a strong guarantee for the safe and stable operation of the power grid.

[0107] Preferably, Figure 3 As shown, the accumulated power outage events can be queried, reset, and the corresponding accumulated power outage event list can be exported according to the unit, power outage type, and power outage status. The accumulated power outage event list includes status, fault number, line name, unit name, type, power outage start time, and power outage end time.

[0108] Preferably, Figure 6 As shown, the affected cell includes sequence number, status, cell name, power outage start time, power outage end time, cell address, contact person, and contact information.

[0109] Preferably, Figure 4 As shown, the power outage users include high-voltage users who have power supplied and those who have not, low-voltage users who have power supplied and those who have not, low-voltage non-residential users who have power supplied and those who have not, and sensitive users who have power supplied and those who have not. A list of power outage users can be exported, and the list of power outage users includes serial number, account number, account name, electricity usage address, sensitive users, user classification, industry classification, electricity usage category, power outage start time, and power outage end time.

[0110] Preferably, Figure 5 As shown, the sensitive user includes serial number, user information, and user manager information. The user information includes user number, user name, electricity address, contact information, backup number, user tag, and user sensitivity. The user manager information includes name, contact information, and position.

[0111] The present invention achieves a more comprehensive understanding of the scope and extent of the impact of power outages, and performs visual statistics and analysis of power outage information in the monitoring area, including viewing the overall distribution and quantity of power outages in the entire network, as well as statistical information on specific affected substations, lines, transformers, users, communities, etc., and can export relevant detailed information, such as focusing on sensitive users. Sensitive users defined in this technical solution are users who have complained more than twice, repaired more than twice, and experienced power outages more than twice in a week within a year. Targeted attention is paid to these users to increase the satisfaction of end customers. This information is crucial for formulating effective power outage response strategies and optimizing power grid operation and maintenance plans.

[0112] The preferred embodiments of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above embodiments. Various changes can be made within the knowledge scope of ordinary technicians in the field without departing from the purpose of the present invention. These changes involve related technologies well known to those skilled in the art, which all fall within the scope of protection of the patent of the present invention.

[0113] Many other changes and modifications may be made without departing from the concept and scope of the present invention.It should be understood that the present invention is not limited to the specific embodiments, and the scope of the present invention is defined by the appended claims.

Claims

1. A power outage analysis and early warning system based on a power grid map, characterized by: It includes an acquisition unit, which acquires fault detection data from the power grid measurement center and the power grid marketing system in real time, and imports the fault detection data into the database of the power outage analysis and early warning platform; The power outage analysis and early warning platform performs data preprocessing, data analysis, and dynamic adjustment of thresholds and early warnings for the fault detection data in the database; The power outage analysis and early warning platform includes a fault power outage unit, a fault work order unit, a power grid one-picture alarm display unit, and an event message queue alarm unit; A fault power outage unit is used to display the power outage information in the monitoring area by category; the fault power outage unit includes cumulative power outage events, main line power outage, branch line power outage, distribution transformer power outage, affected cells, power outage users, sensitive users, and power restoration rate; A fault work order unit is used to display the power outage fault work orders in the monitoring area; the fault work order unit includes a unit bar chart display and a type bar chart display; A grid one-picture alarm display unit displays the power outage situation in the monitoring area based on a grid one-picture; the power outage situation includes power outage in process, power outage repaired, work order in process, work order repaired, and emergency repair station; The event message queue alarm unit is used to display the power outage events in the monitoring area in a carousel and send SMS and email notifications of power outage events.

2. The power outage analysis and early warning system based on a power grid map according to claim 1 is characterized in that: The acquisition unit simultaneously acquires fault detection data from the power grid measurement center and the power grid marketing system through the SpringBoot framework structure and the kafka message queue.

3. The power outage analysis and early warning system based on a power grid map according to claim 2 is characterized in that: The power outage analysis and early warning platform adopts a high-speed data transmission protocol and a distributed processing architecture.

4. The power outage analysis and early warning system based on a power grid map according to claim 3 is characterized in that: The telemetry data dynamically adjusts the threshold using a machine learning neural network regression model.

5. The power outage analysis and early warning system based on a power grid map according to any one of claims 1 to 4, characterized in that: The power outage analysis and early warning platform performs equipment analysis on stations, lines, and transformers in the monitoring area according to the equipment topology relationship, and realizes distribution and quantity statistics by locating the geographical location of the equipment ledger location information on a power grid map. By collecting the list of communities and geographical location information at the social level, matching user information according to the geographical scope, matching the relationship between equipment and communities and users according to the household-transformer relationship, and matching the distribution and quantity statistics of the affected communities and users on a power grid map according to the actual geographical location of the power outage event.

6. The power outage analysis and early warning system based on a power grid map according to claim 5 is characterized in that: The accumulated power outage events can be queried, reset, and the corresponding accumulated power outage event list can be exported according to the unit, power outage type, and power outage status. The accumulated power outage event list includes status, fault number, line name, unit name, type, power outage start time, and power outage end time.

7. The power outage analysis and early warning system based on a power grid map according to claim 6 is characterized in that: The affected cell includes the serial number, status, cell name, power outage start time, power outage end time, cell address, contact person, and contact information.

8. The power outage analysis and early warning system based on a power grid map according to claim 7 is characterized in that: The power outage users include high-voltage users who have power supplied and those who have not, low-voltage users who have power supplied and those who have not, low-voltage non-residential users who have power supplied and those who have not, and sensitive users who have power supplied and those who have not. A list of power outage users can be exported, and the list of power outage users includes serial number, account number, account name, electricity usage address, sensitive users, user classification, industry classification, electricity usage category, power outage start time, and power outage end time.

9. The power outage analysis and early warning system based on a power grid map according to claim 8 is characterized in that: The sensitive user includes serial number, user information, and user housekeeper information. The user information includes user number, user name, electricity address, contact information, backup number, user tag, and user sensitivity. The user housekeeper information includes name, contact information, and position.

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