Visual adaptive power distribution area definition and identification method and system

Abstract

The invention relates to the technical field of power distribution area identification, in particular to a visual self-adaptive power distribution area definition and identification method and system. The scheme comprises the following steps: transmitting data to a data center; a data bin is established in a data center, and data in the data bin is subjected to large-partition and small-partition classification; setting a small partition of each piece of data; setting a large partition of each piece of data; after a power distribution network fault occurs every time, a partition division mode is modified according to the topology after the fault; and performing online display according to a partition division result. According to the scheme, the accurate division and dynamic management of the power distribution area are realized through the modes of deploying the sensors to collect data, establishing the data bin and performing scientific partitioning, dynamically correcting the partitioning after the fault, performing visual display and the like, and the data management, operation and maintenance efficiency of the power distribution network is improved.

Description

Technical Field

[0001] This invention relates to the field of power distribution area identification technology, and more specifically, to a visual adaptive power distribution area definition and identification method and system. Background Technology

[0002] In the field of distribution area identification, research on visualized adaptive distribution area definition and identification typically involves deploying numerous smart sensors within the distribution network to collect real-time electrical data such as current, voltage, and power, as well as non-electrical data such as geographic information and load distribution. Big data analytics and artificial intelligence algorithms are then used to deeply mine this data, combining it with the distribution network's topology to automatically define distribution areas based on specific rules and algorithms, achieving accurate identification of area boundaries. Simultaneously, visualization technology is used to display the distribution areas in an intuitive map format, marking area boundaries, key nodes, and equipment information, providing a clear overview for operation and maintenance personnel. Its significance lies in enabling flexible adjustments to distribution areas based on the real-time operating status and load changes of the distribution network, improving power supply reliability and energy distribution efficiency, and reducing operation and maintenance costs. With the continuous expansion of distribution network scale and increasing structural complexity, along with the large-scale integration of distributed energy resources, visualized adaptive distribution area definition and identification are of great importance for ensuring the safe, stable, and economical operation of the distribution network.

[0003] Prior to this invention, existing methods for defining and identifying visual adaptive distribution areas primarily relied on manual experience combined with simple Geographic Information Systems (GIS) for area division, using fixed thresholds to identify distribution area boundaries. The technical challenge lies in adapting to the rapidly changing operating states and complex, diverse load characteristics of the distribution network. Traditional methods cannot capture the dynamic changes of electrical and non-electrical quantities in real time and accurately, leading to unreasonable area division and low identification accuracy. Furthermore, high human involvement results in low efficiency, and the visualization is neither intuitive nor comprehensive. The key lies in developing efficient data analysis algorithms to achieve real-time processing and analysis of massive amounts of data; establishing intelligent adaptive models that can automatically adjust distribution areas according to changes in the distribution network; and creating a powerful visualization platform to improve the human-computer interaction experience. Summary of the Invention

[0004] In view of the above problems, this invention proposes a visual adaptive distribution area definition and identification method and system. By deploying sensors to collect data, establishing a data warehouse and scientifically partitioning the area, dynamically correcting the partitioning after a fault, and visualizing the display, the method achieves accurate division and dynamic management of distribution areas, thereby improving the data management and operation and maintenance efficiency of the distribution network.

[0005] According to a first aspect of the present invention, a method for defining and identifying a visual adaptive power distribution area is provided.

[0006] In one or more embodiments, preferably, the method for defining and identifying a visual adaptive power distribution area includes:

[0007] Transmit the data to the data center;

[0008] Establish a data warehouse in the data center, and classify the data within the data warehouse into large and small partitions;

[0009] Configure small partition settings for each data item;

[0010] Set up large partitions for each data item;

[0011] After each distribution network fault occurs, the partitioning method is modified according to the post-fault topology.

[0012] The results of the partitioning will be displayed online.

[0013] In one or more embodiments, preferably, the step of transmitting data to the data center specifically includes:

[0014] Voltage transformers are installed at nodes on the power distribution network;

[0015] Current transformers are installed on circuit breakers, disconnect switches, and pre-designated critical lines of power distribution lines;

[0016] The collected data is fed back to the data center in real time.

[0017] In one or more embodiments, preferably, the step of establishing a data warehouse in a data center and classifying the data within the data warehouse into large and small partitions specifically includes:

[0018] Set up a data warehouse in the data center;

[0019] Set up large and small partitions within the data warehouse.

[0020] In one or more embodiments, preferably, the setting of small partitions for each piece of data specifically includes:

[0021] All 10kV busbars are obtained based on the pre-set distribution network topology diagram;

[0022] For the measurement data of each 10kV bus downstream, set up a corresponding sub-zone.

[0023] In one or more embodiments, preferably, setting a large partition for each piece of data specifically includes:

[0024] Large zones are divided into top-level large zones, large zones, medium-level zones, and low-level zones according to voltage level.

[0025] Areas exceeding 500kV are designated as top-level large zones, which are pre-defined.

[0026] The 220kV voltage level is divided into major zones based on the nearest busbar.

[0027] For 110kV voltage levels, the nearest busbar is used as the medium-level zone;

[0028] For the 35kV voltage level, the nearest busbar is used as the lower-level zone.

[0029] In one or more embodiments, preferably, modifying the partitioning method according to the post-fault topology after each distribution network fault specifically includes:

[0030] Automatic fault identification is performed after each fault occurs;

[0031] Reconstruct the power distribution network based on the fault identification results;

[0032] The large and small zones are corrected based on the restructured distribution network.

[0033] In one or more embodiments, preferably, the online display based on the partitioning results specifically includes:

[0034] After obtaining the partitioning results of the corrected partitions, the partitions are automatically numbered, including a large partition and a small partition.

[0035] The partition number is used to mark and display data in the backend interface and the data warehouse of the data center.

[0036] According to a second aspect of the present invention, a visual adaptive power distribution area definition and identification system is provided.

[0037] In one or more embodiments, preferably, the visual adaptive power distribution area definition and identification system includes:

[0038] The data transmission module is used to transmit data to the data center;

[0039] The data warehouse creation module is used to build a data warehouse in the data center and classify the data within the data warehouse into large and small partitions;

[0040] The partitioning settings module is used to configure the sub-partition settings for each piece of data;

[0041] The large partition settings module is used to set the large partition for each piece of data;

[0042] The partitioning module is modified to change the partitioning method according to the post-fault topology after each distribution network fault.

[0043] The online display module is used to display the results of the partitioning online.

[0044] According to a third aspect of the present invention, a computer-readable storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement the method as described in any one of the first aspects of the present invention.

[0045] According to a fourth aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method described in any one aspect of the present invention.

[0046] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0047] In this invention, a hierarchical and partitioned data management approach can systematically and meticulously organize massive amounts of data, facilitating rapid data retrieval and analysis, improving data processing efficiency, and providing a reliable data foundation for the definition and identification of power distribution areas.

[0048] In this invention, by using dynamic post-fault correction zoning and visualization, maintenance personnel can monitor the distribution network zoning status in real time, quickly locate fault areas, achieve efficient operation and maintenance, and improve power supply reliability and power distribution efficiency.

[0049] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings.

[0050] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart of a method for defining and identifying a visual adaptive power distribution area according to an embodiment of the present invention.

[0053] Figure 2This is a flowchart illustrating the process of transmitting data to a data center in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0054] Figure 3 This is a flowchart illustrating a method for defining and identifying a visual adaptive power distribution area according to an embodiment of the present invention, which involves establishing a data warehouse in a data center and classifying the data within the data warehouse into large and small partitions.

[0055] Figure 4 This is a flowchart illustrating the setting of small partitions for each data point in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0056] Figure 5 This is a flowchart illustrating the setting of large partitions for each data point in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0057] Figure 6 This is a flowchart illustrating how, in a visual adaptive distribution area definition and identification method according to an embodiment of the present invention, the partitioning method is modified based on the post-fault topology after each distribution network fault occurs.

[0058] Figure 7 This is a flowchart illustrating the online display of partitioning results in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0059] Figure 8 This is a structural diagram of a visual adaptive power distribution area definition and identification system according to an embodiment of the present invention.

[0060] Figure 9 This is a structural diagram of an electronic device according to one embodiment of the present invention. Detailed Implementation

[0061] In some of the processes described in the specification, claims, and accompanying drawings of this invention, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to different types.

[0062] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] In the field of distribution area identification, research on visualized adaptive distribution area definition and identification typically involves deploying numerous smart sensors within the distribution network to collect real-time electrical data such as current, voltage, and power, as well as non-electrical data such as geographic information and load distribution. Big data analytics and artificial intelligence algorithms are then used to deeply mine this data, combining it with the distribution network's topology to automatically define distribution areas based on specific rules and algorithms, achieving accurate identification of area boundaries. Simultaneously, visualization technology is used to display the distribution areas in an intuitive map format, marking area boundaries, key nodes, and equipment information, providing a clear overview for operation and maintenance personnel. Its significance lies in enabling flexible adjustments to distribution areas based on the real-time operating status and load changes of the distribution network, improving power supply reliability and energy distribution efficiency, and reducing operation and maintenance costs. With the continuous expansion of distribution network scale and increasing structural complexity, along with the large-scale integration of distributed energy resources, visualized adaptive distribution area definition and identification are of great importance for ensuring the safe, stable, and economical operation of the distribution network.

[0064] Prior to this invention, existing methods for defining and identifying visual adaptive distribution areas primarily relied on manual experience combined with simple Geographic Information Systems (GIS) for area division, using fixed thresholds to identify distribution area boundaries. The technical challenge lies in adapting to the rapidly changing operating states and complex, diverse load characteristics of the distribution network. Traditional methods cannot capture the dynamic changes of electrical and non-electrical quantities in real time and accurately, leading to unreasonable area division and low identification accuracy. Furthermore, high human involvement results in low efficiency, and the visualization is neither intuitive nor comprehensive. The key lies in developing efficient data analysis algorithms to achieve real-time processing and analysis of massive amounts of data; establishing intelligent adaptive models that can automatically adjust distribution areas according to changes in the distribution network; and creating a powerful visualization platform to improve the human-computer interaction experience.

[0065] This invention provides a method and system for defining and identifying visual adaptive power distribution areas. This solution achieves accurate division and dynamic management of power distribution areas by deploying sensors to collect data, establishing a data warehouse and scientifically partitioning the data, dynamically correcting partitions after faults, and providing visual display, thereby improving the efficiency of power distribution network data management and operation and maintenance.

[0066] According to a first aspect of the present invention, a method for defining and identifying a visual adaptive power distribution area is provided.

[0067] Figure 1 This is a flowchart of a method for defining and identifying a visual adaptive power distribution area according to an embodiment of the present invention.

[0068] In one or more embodiments, preferably, the method for defining and identifying a visual adaptive power distribution area includes:

[0069] S101. Transmit the data to the data center;

[0070] S102. Establish a data warehouse in the data center and classify the data in the data warehouse into large and small partitions;

[0071] S103, Configure the small partition settings for each data item;

[0072] S104. Set up a large partition for each data item;

[0073] S105. After each distribution network fault occurs, modify the partitioning method according to the post-fault topology.

[0074] S106. Display the partitioning results online.

[0075] In this embodiment of the invention, instrument transformers are deployed at distribution network nodes and critical lines to collect data and transmit it to a data center. A data warehouse is established in the data center, dividing the network into large zones according to voltage levels and smaller zones according to the distribution network topology. After a distribution network fault occurs, the fault is automatically identified and the network is reconstructed, the zone division is corrected, and the new zones are numbered and displayed in the background interface and data warehouse, providing support for distribution area management.

[0076] Figure 2 This is a flowchart illustrating the process of transmitting data to a data center in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0077] like Figure 2 As shown, in one or more embodiments, preferably, the step of transmitting data to the data center specifically includes:

[0078] S201. Install voltage transformers at node locations on the power distribution network;

[0079] S202. Install current transformers on circuit breakers, disconnectors and pre-set critical lines of power distribution lines.

[0080] S203. Feed the real-time collected data back to the data center.

[0081] In this embodiment of the invention, voltage transformers are installed at various nodes in the power distribution network. For example, voltage transformers are installed at key nodes such as the outgoing terminals of transformers and load concentration points in the power distribution network. Their function is to proportionally convert the high voltage in the power distribution network into a low voltage signal that can be used for measurement, protection, and control, so as to facilitate subsequent voltage data acquisition and analysis. Simultaneously, current transformers are installed on circuit breakers, disconnectors, and pre-defined key lines on the power distribution lines, as determined by professionals based on a comprehensive evaluation of the power distribution network topology and historical fault data. Current transformers can proportionally convert large currents in the power distribution lines into smaller currents, facilitating the measurement and recording of current data. The voltage and current transformers collect voltage and current data from the power distribution network in real time and stably and accurately feed the collected real-time data back to the data center via wired communication lines (such as optical fibers and cables) or wireless communication technologies (such as 4G / 5G, LoRa, etc.). As the core location for data storage and processing, data centers possess powerful data receiving, storage, and preliminary processing capabilities. They can classify, store, and perform preliminary analysis on received data, providing a data foundation for subsequent power distribution area definition and identification.

[0082] Figure 3 This is a flowchart illustrating a method for defining and identifying a visual adaptive power distribution area according to an embodiment of the present invention, which involves establishing a data warehouse in a data center and classifying the data within the data warehouse into large and small partitions.

[0083] like Figure 3 As shown, in one or more embodiments, preferably, the step of establishing a data warehouse in the data center and classifying the data within the data warehouse into large and small partitions specifically includes:

[0084] S301. Set up a data warehouse in the data center;

[0085] S302. Set up large and small partitions within the data warehouse.

[0086] In this embodiment of the invention, a data warehouse is built within a data center. The data warehouse is a centralized storage repository for storing and managing large amounts of data, similar to a large data warehouse, used to store massive amounts of data collected from various sensors in the power distribution network. Specifically, the data within the data warehouse is first divided into large partitions based on its source, type, or purpose. For example, the data can be divided into electrical quantity data partitions and non-electrical quantity data partitions. The electrical quantity data partition stores data such as voltage, current, and power collected by voltage transformers, current transformers, etc., while the non-electrical quantity data partition stores data such as geographical information and load distribution. After completing the large partition settings, the data within each large partition is further subdivided into smaller partitions. Taking the electrical quantity data partition as an example, it can be further divided into real-time voltage data partitions, historical current data partitions, power fluctuation data partitions, etc. This combination of large and small partitions enables orderly management of the data within the data warehouse, facilitating rapid and accurate data retrieval and processing, and providing efficient data support for the definition and identification of visualized adaptive power distribution areas.

[0087] Figure 4 This is a flowchart illustrating the setting of small partitions for each data point in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0088] like Figure 4 As shown, in one or more embodiments, preferably, the setting of small partitions for each data item specifically includes:

[0089] S401. Obtain all 10kV busbars according to the pre-set distribution network topology diagram;

[0090] S402. For the measurement point data of each 10kV bus downstream, set its corresponding sub-zone.

[0091] In this embodiment of the invention, firstly, a precise distribution network topology map is drawn using a Geographic Information System (GIS) or distribution network design software, based on parameters such as the actual equipment connection relationships and line routes of the distribution network. This topology map visually presents the connection structure of various devices and lines in the distribution network. By analyzing the topology map, all 10kV buses are identified and acquired. 10kV buses are key electrical connection points in the distribution network used to collect and distribute 10kV voltage level electrical energy. For example, in a regional distribution network topology map, 10kV buses within multiple substations and at intermediate nodes of lines can be clearly seen. After acquiring the 10kV buses, data from downstream measurement points is collected for each 10kV bus. This measurement data includes, but is not limited to, electrical quantity data collected by devices such as voltage transformers and current transformers installed on the downstream distribution lines of that bus, as well as non-electrical quantity data such as load distribution collected by intelligent sensors. Taking a specific 10kV busbar as an example, all data collected from its downstream measuring points are integrated, and a corresponding sub-partition is set for these data, such as named "XX 10kV Busbar Measuring Point Data Sub-partition". In this way, a dedicated sub-partition is established for the measuring point data of each 10kV busbar, realizing refined classification and management of data. This enables the rapid location and retrieval of data related to the same busbar during subsequent distribution area definition and identification, improving data processing efficiency and analysis accuracy.

[0092] Figure 5 This is a flowchart illustrating the setting of large partitions for each data point in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0093] like Figure 5 As shown, in one or more embodiments, preferably, setting a large partition for each data item specifically includes:

[0094] S501 classifies large zones according to voltage level into top-level large zones, large zones, medium zones, and low-level zones.

[0095] S502. Areas exceeding 500kV are designated as top-level large zones, and these top-level large zones are pre-configured.

[0096] S503, The 220kV voltage level is divided into major zones based on the nearest busbar;

[0097] S504. For 110kV voltage levels, the nearest busbar is used as the medium-sized zone.

[0098] S505, for 35kV voltage levels, the nearest busbar is used as the lower-level zone.

[0099] In this embodiment of the invention, during the data management process in the data center, data is divided into large partitions based on voltage levels. These large partitions are further subdivided into top-level large partitions, large partitions, medium partitions, and low-level partitions. The top-level large partition is used to store data from areas with voltages exceeding 500kV. Voltage levels of 500kV and above fall under the category of ultra-high voltage transmission, primarily used for large-scale, long-distance power transmission. For example, in areas covered by hub substations and surrounding transmission lines in cross-regional power transmission projects, a top-level large partition is pre-set in the data warehouse, and various data collected by sensors within this area, such as voltage, current, and power, are categorized into the top-level large partition. For areas with a 220kV voltage level, large partitions are set up based on the nearest busbar. A busbar is a node in the power system that collects and distributes electrical energy. For example, in a city power grid, data from corresponding areas is divided into different large partitions based on the different busbars connected to the 220kV transmission lines. For areas with a 110kV voltage level, a medium-level partition is set up based on the nearest busbar. This voltage level is commonly used for power distribution within urban areas. For example, in a city's power supply network, data for this area is classified into the corresponding medium-level partition based on the 110kV busbar. For areas with a 35kV voltage level, a low-level partition is set up based on the nearest busbar. 35kV voltage is generally used for power supply in suburban areas and towns. For example, in a town's distribution network, data for this area is organized into the corresponding low-level partition according to the distribution of 35kV busbars. This method of dividing large partitions by voltage level and busbar allows for systematic and hierarchical classification and management of data, facilitating targeted analysis and processing of power distribution in areas with different voltage levels.

[0100] Figure 6 This is a flowchart illustrating how, in a visual adaptive distribution area definition and identification method according to an embodiment of the present invention, the partitioning method is modified based on the post-fault topology after each distribution network fault occurs.

[0101] like Figure 6 As shown, in one or more embodiments, preferably, modifying the partitioning method according to the post-fault topology after each distribution network fault specifically includes:

[0102] S601. Automatically identify faults after each fault occurs;

[0103] S602. Reconstruct the distribution network based on the fault identification results;

[0104] S603. Perform large and small zone corrections based on the reconstructed distribution network.

[0105] In this embodiment of the invention, when a fault occurs during the operation of the distribution network, a fault identification system pre-deployed in the data center automatically initiates the fault identification procedure. This system analyzes data collected and transmitted in real time by current transformers and voltage transformers installed on the distribution lines, and combines this with the distribution network topology diagram for judgment. For example, when a section of the line experiences an abnormal surge in current and a sudden drop in voltage exceeding the normal fluctuation threshold, the system can determine that the line has a fault and locate the fault point. After fault identification is completed, based on the results, the system restructures the distribution network, adjusting its operation mode by controlling the opening and closing states of circuit breakers, disconnect switches, and other equipment to isolate the faulty area and reconnect the non-faulty areas to form a new power supply network structure. Taking a short-circuit fault on a 10kV distribution line as an example, the system disconnects the circuit breakers at both ends of the faulty line, isolating the faulty line, and simultaneously closes adjacent tie switches, transferring power from the faulty line to other normal lines, thus completing the distribution network restructuring. After the distribution network restructuring, the system corrects the original large and small zones according to the restructured distribution network topology. Specifically, if the original large partition contains a faulty area, after the faulty area is isolated, the data of the remaining area is reclassified into the large partition based on voltage level and bus distribution. For example, if a part of an area originally belonging to the 220kV voltage level large partition is isolated due to a fault, and if it meets the classification criteria for the 110kV voltage level, then that part of the data is transferred to the corresponding 110kV medium partition. For small partitions, the corresponding relationships are also reset based on the changes in the downstream measurement point data of each bus after reconstruction. For example, if the downstream power supply range of a 10kV bus changes after the distribution network reconstruction, and the measurement point data also changes accordingly, then a new small partition is set for that bus to accommodate the new measurement point data. Through the above steps, the partitioning method can be modified in a timely manner after each distribution network fault, ensuring that the partitioning always matches the actual operating state of the distribution network and providing effective data support for the accurate identification and management of subsequent distribution areas.

[0106] Figure 7 This is a flowchart illustrating the online display of partitioning results in a visual adaptive power distribution area definition and identification method according to an embodiment of the present invention.

[0107] like Figure 7 As shown, in one or more embodiments, preferably, the online display based on the partitioning results specifically includes:

[0108] S701. After obtaining the partitioning results of the corrected partition, the partitions are automatically numbered, including a large partition and a small partition.

[0109] S702. Mark and display the partition number in the backend interface and the data warehouse of the data center.

[0110] In this embodiment of the invention, after the distribution network is divided or modified, the system automatically numbers the new partitions. The numbering rule adopts a combination of "large partition - small partition", where the large partitions are divided according to voltage level, such as top-level large partition, large partition, medium partition, and low-level partition, and the small partitions are set according to specific bus and measurement point data. Taking a certain actual scenario as an example, under a large partition of a certain 220kV voltage level, there is a large partition numbered "220kV - 1", and the small partition corresponding to a certain 10kV bus in this large partition is numbered "10kV - 1", then the complete number of this partition is "220kV- 1 - 10kV - 1". After the numbering is completed, the system will mark and display it on the background interface and the data warehouse of the data center. In the backend interface, visualization technology combines the distribution network topology map with partition numbers, using different colors, shapes, or highlighting effects to distinguish different partitions. The partition numbers are also labeled at corresponding locations on the topology map. Maintenance personnel can intuitively view the distribution and numbering of each partition within the distribution network by logging into the backend management system. Within the data warehouse of the data center, each data storage unit is labeled with its corresponding partition number. For example, a storage unit storing measurement data for a 10kV busbar will clearly indicate its partition number as "220kV - 1 - 10kV - 1" in its data attributes, facilitating data retrieval and management. This partition numbering and display method enables maintenance and management personnel to quickly understand the distribution network partitioning results, effectively linking data with actual distribution areas and improving distribution network management efficiency.

[0111] According to a second aspect of the present invention, a visual adaptive power distribution area definition and identification system is provided.

[0112] Figure 8 This is a structural diagram of a visual adaptive power distribution area definition and identification system according to an embodiment of the present invention.

[0113] In one or more embodiments, preferably, the visual adaptive power distribution area definition and identification system includes:

[0114] Data transmission module 801 is used to transmit data to the data center;

[0115] The data warehouse creation module 802 is used to create a data warehouse in the data center and classify the data within the data warehouse into large and small partitions.

[0116] Partitioning module 803 is used to set the sub-partition settings for each piece of data;

[0117] The large partition setting module 804 is used to set the large partition for each piece of data;

[0118] Modify the partitioning module 805 to modify the partitioning method according to the post-fault topology after each distribution network fault.

[0119] The online display module 806 is used to display the results of the partitioning online.

[0120] In this embodiment of the invention, a system suitable for different structures is realized through a series of modular designs. This system can achieve closed-loop, reliable, and efficient execution through data acquisition, analysis, and control.

[0121] According to a third aspect of the present invention, a computer-readable storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement the method as described in any one of the first aspects of the present invention.

[0122] According to a fourth aspect of the present invention, an electronic device is provided. Figure 9 This is a structural diagram of an electronic device according to one embodiment of the present invention. Figure 9 The electronic device shown is a general-purpose visual adaptive power distribution area definition and identification device. For example... Figure 9 As shown, the electronic device 900 includes a central processing unit (CPU) 901, which can perform various appropriate actions and processes according to computer program instructions stored in read-only memory (ROM) 902 or loaded from storage unit 908 into random access memory (RAM) 903. The RAM 903 may also store various programs and data required for the operation of the electronic device 900. The CPU 901, ROM 902, and RAM 903 are interconnected via bus 904. An input / output (I / O) interface 905 is also connected to bus 904.

[0123] Multiple components in electronic device 900 are connected to I / O interface 905, including: input unit 906, output unit 907, and storage unit 908. Processing unit 901 executes the various methods and processes described above, such as the methods described in the first aspect of embodiments of the present invention. For example, in some embodiments, the methods described in the first aspect of embodiments of the present invention can be implemented as computer software programs stored in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 900 via ROM 902 and / or communication unit 909. When the computer program is loaded into RAM 903 and executed by CPU 901, one or more operations of the methods described in the first aspect of embodiments of the present invention can be performed. Alternatively, in other embodiments, CPU 901 can be configured to perform one or more operations of the methods described in the first aspect of embodiments of the present invention by any other suitable means (e.g., by means of firmware).

[0124] The technical solutions provided by the embodiments of the present invention may include the following beneficial effects:

[0125] In this invention, a hierarchical and partitioned data management approach can systematically and meticulously organize massive amounts of data, facilitating rapid data retrieval and analysis, improving data processing efficiency, and providing a reliable data foundation for the definition and identification of power distribution areas.

[0126] In this invention, by using dynamic post-fault correction zoning and visualization, maintenance personnel can monitor the distribution network zoning status in real time, quickly locate fault areas, achieve efficient operation and maintenance, and improve power supply reliability and power distribution efficiency.

[0127] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0128] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0129] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0130] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0131] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for defining and identifying visual adaptive power distribution areas, characterized in that, The method includes: Transmit the data to the data center; Establish a data warehouse in the data center, and classify the data within the data warehouse into large and small partitions; Configure small partition settings for each data item; Set up large partitions for each data item; After each distribution network fault occurs, the partitioning method is modified according to the post-fault topology. The results of the partitioning will be displayed online.

2. The method for defining and identifying a visual adaptive power distribution area as described in claim 1, characterized in that, The process of transmitting data to the data center specifically includes: Voltage transformers are installed at nodes on the power distribution network; Current transformers are installed on circuit breakers, disconnect switches, and pre-designated critical lines of power distribution lines; The collected data is fed back to the data center in real time.

3. The method for defining and identifying a visual adaptive power distribution area as described in claim 1, characterized in that, The establishment of a data warehouse in the data center, and the classification of data within the data warehouse into large and small partitions, specifically includes: Set up a data warehouse in the data center; Set up large and small partitions within the data warehouse.

4. The method for defining and identifying a visual adaptive power distribution area as described in claim 1, characterized in that, The specific settings for configuring small partitions for each data item include: All 10kV busbars are obtained based on the pre-set distribution network topology diagram; For the measurement data of each 10kV bus downstream, set up a corresponding sub-zone.

5. The method for defining and identifying a visual adaptive power distribution area as described in claim 1, characterized in that, Setting up large partitions for each data item specifically includes: Large zones are divided into top-level large zones, large zones, medium-level zones, and low-level zones according to voltage level. Areas exceeding 500kV are designated as top-level large zones, which are pre-defined. The 220kV voltage level is divided into major zones based on the nearest busbar. For 110kV voltage levels, the nearest busbar is used as the medium-level zone; For the 35kV voltage level, the nearest busbar is used as the lower-level zone.

6. The method for defining and identifying a visual adaptive power distribution area as described in claim 1, characterized in that, The modification of the partitioning method based on the post-fault topology after each distribution network fault includes: Automatic fault identification is performed after each fault occurs; Reconstruct the power distribution network based on the fault identification results; The large and small zones are corrected based on the restructured distribution network.

7. The method for defining and identifying a visual adaptive power distribution area as described in claim 1, characterized in that, The online display based on the partitioning results specifically includes: After obtaining the partitioning results of the corrected partitions, the partitions are automatically numbered, including a large partition and a small partition. The partition number is used to mark and display data in the backend interface and the data warehouse of the data center.

8. A visual adaptive power distribution area definition and identification system, characterized in that, The system is used to implement the method as described in any one of claims 1-7, the system comprising: The data transmission module is used to transmit data to the data center; The data warehouse creation module is used to build a data warehouse in the data center and classify the data within the data warehouse into large and small partitions; The partitioning settings module is used to configure the sub-partition settings for each piece of data; The large partition settings module is used to set the large partition for each piece of data; The partitioning module is modified to change the partitioning method according to the post-fault topology after each distribution network fault. The online display module is used to display the results of the partitioning online.

9. A computer-readable storage medium storing computer program instructions thereon, characterized in that, The computer program instructions, when executed by a processor, implement the method as described in any one of claims 1-7.

10. An electronic device comprising a memory and a processor, characterized in that, The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method as described in any one of claims 1-7.

Images