Power distribution network panoramic dynamic topology atomic-scale service implementation method and system based on service driving, electronic equipment, computer readable storage medium and computer program product

Abstract

The invention discloses a power distribution network panoramic dynamic topology atomic-scale service implementation method and system based on business driving, electronic equipment, a computer readable storage medium and a computer program product, and the method comprises the steps: carrying out the matching of a corresponding atomic-scale topology service according to a service call request of an upper business system; matching a topology constraint condition according to the atomic-scale topology service, and analyzing into a graph database query statement based on the topology constraint condition; executing the graph database query statement, and screening out nodes and edges meeting topological constraint conditions from a graph database; obtaining an atomic service result based on the nodes and the edges meeting the topology constraint conditions; and returning the atomic service result to the upper layer service system.

Description

Technical Field

[0001] This invention belongs to the field of power grid digitalization technology, specifically a business-driven method, system, electronic device, computer-readable storage medium, and computer program product for implementing atomic-level services of panoramic dynamic topology of distribution network. Background Technology

[0002] Distribution network topology is the core foundation for distribution network operation monitoring, fault handling, and planning optimization. With the construction of enterprise-level real-time measurement centers, the scale of distribution network data has surged, and traditional distribution network topology services can no longer meet diversified business needs. The main technical problems are as follows:

[0003] 1) Coarse service granularity and poor business adaptability

[0004] Traditional distribution network topology services mostly adopt a "full topology push" model, relying on relational databases to store device ledgers and connection relationships. This model can only provide a full static topology at the regional level and cannot be tailored to specific business scenarios. For example, power outage analysis requires the topology around the faulty equipment, and line loss calculation requires segmented line topology. Traditional services require custom development of topology filtering modules. This results in long development cycles and makes it difficult to quickly respond to business needs.

[0005] 2) Difficulty in integrating multi-source data and poor consistency of topological data.

[0006] Distribution network topology data comes from heterogeneous sources, including equipment ledgers in relational databases (such as asset IDs and equipment types), dynamic data from real-time measurement centers (such as switch status, voltage, and current), and alarm data from equipment status monitoring systems (such as fault signals). Existing technologies lack a unified data mapping mechanism, and data from different systems is stored independently. This easily leads to problems such as mismatches between ledger equipment and real-time measurement equipment, and a disconnect between topology connections and actual operating status. Data consistency error rates reach 5%-8%, affecting the reliability of topology services.

[0007] 3) Low service reusability and serious waste of resources.

[0008] Different business scenarios (such as fault diagnosis and planning assistance) require the repeated development of topology calculation modules: for example, fault diagnosis requires the development of a power point tracing module, and power outage analysis requires the development of a power outage range calculation module. The modules cannot be reused, resulting in high server resource utilization, with duplicate modules accounting for up to 40%, and increased operation and maintenance costs.

[0009] While some existing solutions attempt to optimize topology storage through graph databases, they fail to address core issues such as dynamic binding of business needs with topology features and automatic synchronization of multi-source data. Consequently, they cannot meet the demands of enterprise-level real-time measurement centers for high-precision, highly adaptable, and highly reusable topology services. Summary of the Invention

[0010] Purpose of the Invention: To address the problems of coarse granularity in traditional distribution network topology services, which cannot adapt to the segmented needs of multiple business scenarios such as power outage analysis and line loss calculation; to solve the problems of difficulty in integrating multi-source heterogeneous data such as relational ledgers, real-time measurements, and equipment status, resulting in poor topology data consistency; and to solve the problem of low reusability of topology services, requiring repeated development of calculation modules, this invention proposes a business-driven method, system, electronic device, computer-readable storage medium, and computer program product for implementing atomic-level services of distribution network panoramic dynamic topology. This enables the standardization and flexible invocation of atomic-level services, reduces operation and maintenance costs, and is applicable to multiple business scenarios such as power outage analysis, fault diagnosis, and time-sharing and segmented line loss analysis in distribution networks supported by enterprise-level real-time measurement centers.

[0011] Technical Solution: In the first aspect, this invention proposes a business-driven method for implementing atomic-level services of dynamic topology across a distribution network, including:

[0012] Match the corresponding atomic-level topology service based on the service call request from the upper-layer business system;

[0013] Based on the atomic-level topology service, topology constraints are matched, and the topology constraints are parsed into graph database query statements.

[0014] Execute the graph database query statement to filter out nodes and edges that meet the topological constraints from the graph database;

[0015] Based on nodes and edges that meet topological constraints, atomic service results are obtained;

[0016] The atomic service results are returned to the upper-level business system.

[0017] Furthermore, the atomic-level topology service is obtained according to the following steps:

[0018] An atomic-level topology service is encapsulated by defining its name, input parameters, output parameters, and functional description; the input parameters include a rule ID; the specified ID is used to match topology constraints.

[0019] Standardize the interface for atomic-level topology services to obtain the atomic-level topology services available for use.

[0020] Furthermore, the topological constraints are generated according to the following steps;

[0021] Determine the topology constraints for each business scenario and define the required topology output for each business scenario; the topology constraints are obtained based on the business requirements of each business scenario.

[0022] Rules are formed using the topological constraints of each business scenario. Each rule includes: rule ID, business scenario name, topological constraints, and an effectiveness status field. When the effectiveness status field is enabled, the rule is effective.

[0023] Furthermore, the graph database is mapped from a relational database, which stores a device ledger and a device connection relationship table.

[0024] Furthermore, the graph database is obtained by mapping from a relational database, specifically including:

[0025] Using the unique device identifier as the core, define the mapping relationship between relational database fields and graph database attributes;

[0026] By reading the equipment ledger and connection relationship table of the relational database, and using the defined mapping relationship between relational database fields and graph database attributes, the relational database fields are associated with the graph database attributes.

[0027] Furthermore, when the graph database attributes are updated, the corresponding fields in the relational database are updated synchronously.

[0028] Furthermore, after associating relational database fields with graph database attributes, integrity and consistency checks are performed on the associated graph database. Only when both integrity and consistency checks pass can the graph database be obtained for use.

[0029] Secondly, this invention proposes a business-driven, panoramic dynamic topology atomic-level service implementation system for distribution networks, comprising:

[0030] The atomic-level topology service matching module is configured to match the corresponding atomic-level topology service based on the service call request from the upper-layer business system.

[0031] The topology constraint matching module is configured to: match topology constraints based on the atomic-level topology service, and parse the topology constraints into a graph database query statement.

[0032] The filtering module is configured to execute the graph database query statement to filter out nodes and edges that meet the topological constraints from the graph database;

[0033] The atomic service result output module is configured to: obtain atomic service results based on nodes and edges that meet topological constraints; and return the atomic service results to the upper-layer business system.

[0034] Furthermore, the atomic-level topology service is obtained according to the following steps:

[0035] An atomic-level topology service is encapsulated by defining its name, input parameters, output parameters, and functional description; the input parameters include a rule ID; the specified ID is used to match topology constraints.

[0036] Standardize the interface for atomic-level topology services to obtain the atomic-level topology services available for use.

[0037] Furthermore, the topological constraints are generated according to the following steps;

[0038] Determine the topology constraints for each business scenario and define the required topology output for each business scenario; the topology constraints are obtained based on the business requirements of each business scenario.

[0039] Rules are formed using the topological constraints of each business scenario. Each rule includes: rule ID, business scenario name, topological constraints, and an effectiveness status field. When the effectiveness status field is enabled, the rule is effective.

[0040] Furthermore, the graph database is mapped from a relational database, which stores a device ledger and a device connection relationship table.

[0041] Furthermore, the graph database is obtained by mapping from a relational database, specifically including:

[0042] Using the unique device identifier as the core, define the mapping relationship between relational database fields and graph database attributes;

[0043] By reading the equipment ledger and connection relationship table of the relational database, and using the defined mapping relationship between relational database fields and graph database attributes, the relational database fields are associated with the graph database attributes.

[0044] Furthermore, when the graph database attributes are updated, the corresponding fields in the relational database are updated synchronously.

[0045] Furthermore, after associating relational database fields with graph database attributes, integrity and consistency checks are performed on the associated graph database. Only when both integrity and consistency checks pass can the graph database be obtained for use.

[0046] Thirdly, the present invention provides an electronic device, the electronic device comprising:

[0047] At least one processor;

[0048] and a memory communicatively connected to the at least one processor;

[0049] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to execute a business-driven method for implementing atomic-level services of dynamic topology of a distribution network panorama.

[0050] Fourthly, the present invention proposes a computer-readable storage medium storing computer instructions, which are used to enable a processor to implement a business-driven method for implementing atomic-level services of a dynamic topology of a power distribution network panorama.

[0051] Fifthly, the present invention proposes a computer program product, which includes a computer program that, when executed by a processor, implements a business-driven method for implementing atomic-level services of a dynamic topology of a power distribution network panorama.

[0052] Beneficial effects: Compared with the prior art, the present invention has the following advantages:

[0053] (1) Significantly improved business adaptability: Through the dynamic binding of atomic-level services and business rules, the reuse of one service in multiple scenarios can be achieved without repeated development; compared with the traditional customized development model, the adaptation cycle of new business scenarios is significantly shortened and the business response efficiency is improved.

[0054] (2) Resource utilization is significantly improved: the standardized encapsulation of atomic-level services reduces the development of redundant modules, the server CPU utilization rate is reduced by 40%, and the memory utilization rate is reduced by 35%; at the same time, service call monitoring enables dynamic resource scheduling, which alleviates the problem of resource waste.

[0055] (3) Significantly improved data consistency: The multi-source data bidirectional mapping mechanism ensures real-time synchronization between relational data and graph data, significantly reducing the data consistency error rate; the data verification mechanism reduces invalid data input, greatly improving the availability of topology services and meeting the data reliability requirements of enterprise-level real-time measurement centers. Attached Figure Description

[0056] Figure 1 This is a flowchart of the business-driven panoramic dynamic topology atomic-level service method for distribution networks proposed in this invention;

[0057] Figure 2 Flowchart of a multi-source data bidirectional mapping mechanism;

[0058] Figure 3 Flowchart for dynamic adaptation of atomic-level services;

[0059] Figure 4 This is a flowchart of the time-sharing and segmented line loss analysis in Example 2. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of this invention clearer, the following will further explain, in conjunction with the accompanying drawings and embodiments, a business-driven method for implementing atomic-level services of dynamic topology for a distribution network panorama.

[0061] Example 1:

[0062] This invention proposes a business-driven method for implementing atomic-level services of dynamic topology across a distribution network, comprising:

[0063] Match the corresponding atomic-level topology service based on the service call request from the upper-layer business system;

[0064] Based on atomic-level topology services, topology constraints are matched, and the topology constraints are parsed into graph database query statements.

[0065] Execute a graph database query statement to filter out nodes and edges that meet the topological constraints from the graph database;

[0066] Based on nodes and edges that meet the topological constraints, atomic service results are obtained; the atomic service results are then returned to the upper-layer business system.

[0067] This invention enables the reuse of a single service across multiple scenarios through dynamic binding of atomic-level services and business rules, eliminating the need for repetitive development. Compared to traditional custom development models, the adaptation cycle for new business scenarios is significantly shortened, and business response efficiency is improved.

[0068] Example 2:

[0069] This invention proposes a business-driven method for implementing atomic-level services of dynamic topology in a distribution network panorama. Through a four-layer technical architecture—multi-source data fusion, business rule modeling, atomic service encapsulation, and dynamic adaptation invocation—it achieves standardization and business adaptation of atomic-level services for distribution network topology. Figure 1 As shown, the specific steps include:

[0070] Step 1: The multi-source data bidirectional mapping layer realizes the conversion and synchronization of relational and graph data. For example... Figure 2 As shown, the specific operations include:

[0071] S100: Define the data mapping rule base. Using unique device identifiers such as asset IDs as the core, establish mapping relationships between relational data fields and graph data attributes. Relational data fields include, but are not limited to, device type, connection terminal number, and installation location in the MySQL device ledger table, and switch status and voltage value in the real-time measurement data table. Graph data attributes correspond to the device category and installation area attributes of nodes in graph databases such as Neo4j, and the connection terminal and on / off status attributes of edges.

[0072] It supports custom mapping rules, including user-added field correspondences, such as mapping the transformer area number to the transformer area attribute of the node. It can adapt to the ledger specifications of different regional distribution networks, has a wide range of applications, and the rules are stored in XML configuration files for easy maintenance.

[0073] S110: Develop a data transformation engine, including forward transformation (relational data → graph data), reverse synchronization (graph data → relational data), and data validation.

[0074] The positive conversion includes:

[0075] The device ledger and connection relationship table of the relational database are read through the JDBC interface, and real-time measurement data is subscribed to through the Kafka message queue.

[0076] Call the mapping rule library to associate relational data fields with graph data attributes, for example, "Equipment type = distribution transformer" corresponds to the node "Equipment category = distribution transformer".

[0077] Create nodes with device attributes and edges with connection attributes in the graph database. For example, generate a node with "device asset ID=1001" and generate an edge with "terminal number=A1" and "terminal number=B1" of "asset ID=1002".

[0078] The reverse synchronization includes: when graph data is updated, such as when topological changes cause the edge's "on / off status" to change, a synchronization thread is triggered to automatically update the corresponding "on / off status" field in the relational database, with a synchronization delay of no more than 1 second.

[0079] Among them, data verification is to perform integrity verification on the transformed data, check whether the nodes are missing key attributes such as "asset ID" and "equipment category", and consistency verification checks whether the connection relationship of the edges forms a closed loop. If the verification fails, a retry is triggered, up to 3 times. If the retry fails, an alarm is sent to the operation and maintenance platform.

[0080] Step 2: The business-driven topology rule base layer binds business and topology requirements, transforming them into parsable constraints. Specifically, this includes:

[0081] S200: Typical Business Scenario Requirements Analysis

[0082] Business Scenarios Topological requirements and constraints Output Power outage analysis Geographic region = target region AND faulty device = target device Topology subgraph around the faulty device Time-sharing segmented line loss Voltage level = 10kV AND line segment = target segment Segmented line topology and measurement data Fault Analysis Power supply radius ≤ 5km AND Equipment type = switch Fault-associated switch topology

[0083] S210: Define the rule description language, including:

[0084] The business scenario requirements are transformed into parsable constraints using a structured language, with the format: [attribute name]=[value] AND / OR [attribute name]=[value], for example, "Geographic region=a certain city AND voltage level=10kV".

[0085] This forms the rules, which include rule ID, scenario name, constraints, and effective status fields. The rules are stored in a MySQL rule table and can be queried and invoked using SQL statements.

[0086] S220: Dynamically maintain the rule base, including:

[0087] Develop a web-based management interface to support operations and maintenance personnel in adding, modifying, and disabling rules.

[0088] This invention supports dynamically adding new business scenarios without modifying the core service code. When adding a rule, the system automatically verifies the syntax correctness, such as whether the attribute name exists, by inputting the scenario name and constraints.

[0089] The rule takes effect by changing the "effective status" to "enabled" without restarting the service.

[0090] Step 3: Based on the Spring Cloud microservice architecture, encapsulate atomic-level topology services, such as... Figure 3 As shown, it includes:

[0091] S300: The atomic emergency service generation framework layer provides standardized, reusable atomic-level topology services.

[0092] Encapsulate no fewer than 30 atomic services, with the key services defined as follows:

[0093] Service Name Input parameters Output parameters Function Description Real-time topology query service Rule ID, Device ID (optional) Node list, edge list, attribute table Output the topology subgraph according to the rules. Historical topology tracing service Timestamp, Device ID Historical moment node / edge attributes Query the topology status for a specified time. Power Point Traceability Service Target device ID Power supply path (node ​​sequence) Tracing the power supply path of the device

[0094] S310: Standardization of design services, including:

[0095] (1) Interface protocol: RESTful API is used, the request method is GET / POST, the request parameters are in JSON format, and the response format includes status code, data, and description fields.

[0096] (2) Version control: The interface URL includes a version number, supports multiple versions in parallel, and facilitates iterative upgrades.

[0097] S320: Service management, including:

[0098] (1) Service registration: Register atomic services to the digital portal through the Eureka component to support service discovery.

[0099] (2) Authorization: Based on the OAuth2.0 protocol, the caller needs to carry a Token request. The Token contains the business system identifier, such as "Power Outage Analysis System", and only the authorized system can call the corresponding service.

[0100] (2) Call monitoring: The number of service calls, response time and failure rate are collected through Prometheus and visualized in Grafana. The response time threshold is set to 3 seconds. An alarm will be triggered if the threshold is exceeded.

[0101] Step 4: Atomic-level service dynamic adaptation layer, achieving precise matching of business and services, and outputting customized results, including:

[0102] S400: Upper-layer business systems, such as power outage analysis systems, send HTTP requests to atomic services, passing in parameters such as rule ID and device ID.

[0103] S410: Rule Matching: Reads constraints from the rule base based on the rule ID and parses them into a graph database query statement, such as the Cypher statement: "MATCH (n:Device) WHERE n.area='a certain city area' RETURN n".

[0104] S420: Topology processing:

[0105] (1) Trimming: Filter nodes and edges according to constraints and remove elements that do not meet the conditions, such as excluding nodes with “voltage level = 0.4kV”.

[0106] (2) Aggregation: For scenarios such as line loss calculation, merge nodes of the same type, such as aggregating distribution transformer nodes of the same line segment into "segment distribution transformer group".

[0107] S430: Result Return: Returns the processed topology data node list and edge list to the caller in a standardized JSON format, with data compressed for transmission (Gzip format) to reduce bandwidth usage.

[0108] This invention addresses the problems of coarse granularity, difficulty in multi-source data fusion, and low reusability in traditional topology services through a four-layer architecture: "multi-source data bidirectional mapping - business rule modeling - atomic service encapsulation - dynamic adaptation and invocation." The system comprises hardware architecture (application server, database server, etc.) and software functional modules (multi-source data fusion, business rule modeling, etc.) to support the method. Specifically, a multi-source data bidirectional mapping mechanism is constructed to achieve the conversion and synchronization of relational and graph data; a business-driven topology rule base is built to transform business requirements into constraints; standardized atomic-level services are encapsulated based on Spring Cloud to provide standardized reusability; and dynamic adaptation of atomic services enables precise "business-service" matching, outputting customized results according to business rules. This method supports multiple scenarios such as power outage analysis and line loss calculation, exhibits low data consistency error rate, and short service response time, making it suitable for distribution network topology services supported by enterprise-level real-time measurement centers.

[0109] Example 3:

[0110] This invention uses a power outage analysis scenario of a 10kV distribution network in a certain area as an example to illustrate the specific implementation process:

[0111] Step 1: Setting up the implementation environment

[0112] (1) Hardware environment: The server uses 2 Intel Xeon E5-2680 v4 (CPU 2.4GHz), 64GB memory, and 1TB SSD.

[0113] (2) Software environment: relational database MySQL 8.0, graph database Neo4j 4.4, microservice framework SpringCloud Alibaba 2021.0.4.0, message queue Kafka 2.8.

[0114] (3) Data preparation: Import 8,200 equipment records from the 10kV distribution network equipment ledger of a certain city, including asset ID, equipment type and installation area, and 12,000 connection records from the connection relationship table. Subscribe to the switch status data of the real-time measurement center and update it every 20 seconds.

[0115] Step 2: Configure multi-source data mapping.

[0116] (1) Configure in the mapping rule base: Asset ID → node “deviceId”, Device type → node “deviceType”, Connection terminal number → edge “terminalNo”, Switch status → edge “state”.

[0117] (2) Start the data conversion engine: Read the MySQL ledger data and generate 8200 Neo4j nodes, such as “deviceId=1001, deviceType=transformer, area=a certain city”, and 12000 edges, such as “terminalNo=A1-A2, state=closed”.

[0118] (3) Data verification: The verification found that three nodes were missing the "area" attribute, which triggered an alarm. After the operation and maintenance personnel completed the data and re-converted it, the data integrity was finally 100%.

[0119] Step 3: Configure Business Rules

[0120] (1) Add a new rule “Power Outage Analysis in a Certain Area” in the rule management interface: rule ID=101, scenario name=Power Outage Analysis in a Certain City, constraint condition=“area=a certain city AND deviceId=faulty device ID”, effective status=enabled.

[0121] (2) The rule parsing engine converts the constraints into Cypher query statements: `MATCH (n:Device)-[r:Connect]-(m:Device) WHERE n.area='a certain city' AND (n.deviceId='faulty device ID' ORm.deviceId='faulty device ID') RETURN n,r,m`.

[0122] Step 4: Atomic Service Invocation and Result Output

[0123] (1) The power outage analysis system sends an HTTP request: `POST / api / v1 / topology / query {"ruleId":"101","deviceId":"1056"}` (faulty device ID=1056, which is the 10kV switch in this area).

[0124] (2) Matching rule 101, execute the Cypher query statement to filter out the fault switch and its associated 210 nodes and 320 edges.

[0125] (3) Topology processing: Prune and exclude nodes that are not in the area, aggregate duplicate connection relationships, and generate a topology subgraph.

[0126] (4) Result return: Returns a list of nodes (including device attributes) and a list of edges (including connection status) in JSON format. The response time is 1.8 seconds and the data size after compression is 200KB.

[0127] (5) Based on the returned topology subgraph, the power outage analysis system calculates the number of users affected by the power outage and completes the power outage range analysis with an accuracy of 98%.

[0128] Step 5: Service reuse verification.

[0129] Call the "Power Point Tracing Service", pass in "deviceId=1056", the service matching rule is "power supply radius ≤ 5km", and return the power supply path (node ​​1056→1032→1001, where 1001 is the substation). The call is successful, verifying the service reusability.

[0130] Example 4:

[0131] This invention uses a time-sharing and segmented line loss analysis scenario as an example to illustrate the specific implementation process:

[0132] The time-sharing and segmented line loss analysis scenario requires obtaining "the topology of a specific segment of a 10kV line and the corresponding time period measurement data", referring to... Figure 4 The specific implementation steps are as follows:

[0133] Business rule configuration: Add a new rule "10kV line segment loss in a certain urban area" in the rule management interface, rule ID=102, scenario name=segment loss analysis, constraint condition="voltage level=10kV AND line segment=L1-03 segment in a certain urban area AND time range=2024-10-01 08:00-10:00", effective status=enabled.

[0134] Rule parsing: Convert the constraints into a Cypher query statement, synchronously associate it with the "15-minute cycle power data" of the real-time measurement center, and generate a compound query logic: `MATCH (n:Device)-[r:Connect]-(m:Device) WHERE En.voltageLevel='10kV' AND n.lineSection='L1-03 section of a certain urban area' RETURN n,r,m UNIONMATCH (p:Measurement) WHERE p.time BETWEEN '2024-10-01 08:00' AND '2024-10-01 10:00' AND p.lineSection='L1-03 section of a certain urban area' RETURN p`.

[0135] Service Request: The line loss analysis system sends an HTTP request: `POST / api / v1 / topology / query {"ruleId":"102","timeRange":"2024-10-01 08:00-10:00"}`.

[0136] Data filtering and association: Execute a compound query statement to filter the topology nodes (including 12 distribution transformers and 3 switches, a total of 15 nodes) and connection edges (22) of the L1-03 section of a certain urban area, and associate them with the power measurement data (8 in total, 15 minutes / data) within the same time period.

[0137] Topology = Measurement Data Binding: Matches the "segmented power value" in the measurement data to the "real-time power" attribute of the corresponding topology node. For example, the distribution transformer node "deviceId=2015" is bound to the 8:00 power value "120kW" and the 8:15 power value "115kW".

[0138] Abnormal data cleaning: One power data point was found to be missing in the 8:30 time period. The data was completed by using the "average of adjacent time periods" method (the average power of 8:15 and 8:45 is 118kW), and the data integrity reached 100%.

[0139] The result returned is a JSON format containing "topology subgraph + time period measurement data", where the topology subgraph is labeled with the power attributes of each node. The response time is 2.2 seconds and the compressed data size is 350KB.

[0140] Results Verification: Based on the returned data, the line loss analysis system uses the "segmented power balance method" to calculate the line loss: total input power of segment L1-03 = 3200 kW·h, total output power = 3024 kW·h, and line loss rate = 5.5%.

[0141] Compared with the manually measured line loss rate (5.3%), the error is ≤0.2%, which meets the accuracy requirements for line loss analysis (error ≤1%), verifying the applicability of the present invention embodiment in segmented line loss scenarios.

[0142] Example 5:

[0143] This invention takes the implementation of a lean planning assistance scenario for a power distribution system as an example to illustrate the specific implementation process in detail:

[0144] The planning assistance scenario requires obtaining "the topology access scheme and load forecast data for newly added distribution transformers in a certain urban area over the next 3 years". The implementation steps are as follows:

[0145] Add a new rule ID=103, scenario name=planning auxiliary analysis, constraint condition=“geographic region=a certain city AND planning year=2025-2027 AND equipment type=new distribution transformer”, and associate it with the “predicted load value” field of the planning load database.

[0146] Call the "Historical Topology Tracing Service" and pass in "timeRange=2021-2023" to obtain three years of historical topology evolution data for a certain city (such as records of new lines and transformer expansion) for load growth trend analysis.

[0147] The planning system sends the following request: `POST / api / v1 / topology / query {"ruleId":"103","loadForecast":"10MW in 2025, 12MW in 2026, 15MW in 2027"}`.

[0148] Based on the constraints, three new distribution transformer access schemes are generated on the existing topology:

[0149] Option 1: Add a new distribution transformer T1 to connect to the existing line L1-04 section;

[0150] Option 2: Add distribution transformers T1 and T2 to connect to sections L1-04 and L1-05 of the line, respectively;

[0151] Option 3: Add a new line segment L1-06 and connect it to distribution transformers T1-T3.

[0152] The system automatically calculates the "power supply radius" and "load rate" indicators for each scheme: Scheme 2 has a power supply radius of ≤3km and a load rate of 65%-75%, which meets the planning requirements (power supply radius ≤5km, load rate ≤80%), and is recommended as the optimal scheme.

[0153] Returns the optimal topology access scheme diagram (including node locations and connection relationships) and load forecast curve, supporting planners in formulating the final scheme and improving planning efficiency.

[0154] Example 6:

[0155] This invention proposes a business-driven, panoramic dynamic topology atomic-level service implementation system for distribution networks, comprising:

[0156] The atomic-level topology service matching module is configured to match the corresponding atomic-level topology service based on the service call request from the upper-layer business system.

[0157] The topology constraint matching module is configured to: match topology constraints based on the atomic-level topology service, and parse the topology constraints into a graph database query statement.

[0158] The filtering module is configured to execute the graph database query statement to filter out nodes and edges that meet the topological constraints from the graph database;

[0159] The atomic service result output module is configured to: obtain atomic service results based on nodes and edges that meet topological constraints; and return the atomic service results to the upper-layer business system.

[0160] In this embodiment of the invention, the atomic-level topology service is obtained according to the following steps:

[0161] An atomic-level topology service is encapsulated by defining its name, input parameters, output parameters, and functional description; the input parameters include a rule ID; the specified ID is used to match topology constraints.

[0162] Standardize the interface for atomic-level topology services to obtain the atomic-level topology services available for use.

[0163] In this embodiment of the invention, the topological constraints are generated according to the following steps;

[0164] Determine the topology constraints for each business scenario and define the required topology output for each business scenario; the topology constraints are obtained based on the business requirements of each business scenario.

[0165] Rules are formed using the topological constraints of each business scenario. Each rule includes: rule ID, business scenario name, topological constraints, and an effectiveness status field. When the effectiveness status field is enabled, the rule is effective.

[0166] In this embodiment of the invention, the graph database is obtained by mapping from a relational database, which stores a device ledger and a device connection relationship table.

[0167] In this embodiment of the invention, the graph database is obtained by mapping from a relational database, specifically including:

[0168] Using the unique device identifier as the core, define the mapping relationship between relational database fields and graph database attributes;

[0169] By reading the equipment ledger and connection relationship table of the relational database, and using the defined mapping relationship between relational database fields and graph database attributes, the relational database fields are associated with the graph database attributes.

[0170] In this embodiment of the invention, when the graph database attribute is updated, the corresponding field in the relational database is updated synchronously.

[0171] In this embodiment of the invention, after associating relational database fields with graph database attributes, integrity and consistency checks are performed on the associated graph database. Only when both integrity and consistency checks pass are the graph database available for use obtained.

[0172] Example 7:

[0173] This embodiment discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps disclosed in any of the above embodiments.

[0174] Example 8:

[0175] This embodiment discloses a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps disclosed in any of the above embodiments.

[0176] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0177] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0178] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A business-driven method for implementing atomic-level services of dynamic topology across a distribution network, characterized in that: include: Match the corresponding atomic-level topology service based on the service call request from the upper-layer business system; Based on the atomic-level topology service, topology constraints are matched, and the topology constraints are parsed into graph database query statements. Execute the graph database query statement to filter out nodes and edges that meet the topological constraints from the graph database; Based on nodes and edges that meet topological constraints, atomic service results are obtained; The atomic service results are returned to the upper-level business system.

2. The method for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven approach according to claim 1, characterized in that: The atomic-level topology service is obtained through the following steps: An atomic-level topology service is encapsulated by defining its name, input parameters, output parameters, and functional description; the input parameters include a rule ID; the specified ID is used to match topology constraints. Standardize the interface for atomic-level topology services to obtain the atomic-level topology services available for use.

3. The method for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven approach according to claim 2, characterized in that: The topological constraints are generated according to the following steps; Determine the topology constraints for each business scenario, and define the required topology output for each business scenario; The topology constraints are derived based on the business requirements of each business scenario. Rules are formed using the topological constraints of each business scenario. The rules include: rule ID, business scenario name, topological constraints, and effective status field. When the effective status field is enabled, the rule is effective.

4. The method for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven approach according to claim 1, characterized in that: The graph database is mapped from a relational database, which stores equipment ledgers and equipment connection relationship tables.

5. The method for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven approach according to claim 4, characterized in that: The graph database is mapped from a relational database and specifically includes: Using the unique device identifier as the core, define the mapping relationship between relational database fields and graph database attributes; By reading the equipment ledger and connection relationship table of the relational database, and using the defined mapping relationship between relational database fields and graph database attributes, the relational database fields are associated with the graph database attributes.

6. The method for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven approach according to claim 5, characterized in that: When the graph database attributes are updated, the corresponding fields in the relational database are updated synchronously.

7. The method for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven approach according to claim 5, characterized in that: After associating relational database fields with graph database attributes, integrity and consistency checks are performed on the associated graph database. Only when both integrity and consistency checks pass can the graph database be obtained for use.

8. A business-driven distribution network panoramic dynamic topology atomic-level service implementation system, characterized in that: include: The atomic-level topology service matching module is configured to match the corresponding atomic-level topology service based on the service call request from the upper-layer business system. The topology constraint matching module is configured to: match topology constraints based on the atomic-level topology service, and parse the topology constraints into a graph database query statement. The filtering module is configured to execute the graph database query statement to filter out nodes and edges that meet the topological constraints from the graph database; The atomic service result output module is configured to: obtain atomic service results based on nodes and edges that meet topological constraints; and return the atomic service results to the upper-layer business system.

9. A business-driven distribution network panoramic dynamic topology atomic-level service implementation system according to claim 8, characterized in that: The atomic-level topology service is obtained through the following steps: An atomic-level topology service is encapsulated by defining its name, input parameters, output parameters, and functional description; the input parameters include a rule ID; the specified ID is used to match topology constraints. Standardize the interface for atomic-level topology services to obtain the atomic-level topology services available for use.

10. A business-driven distribution network panoramic dynamic topology atomic-level service implementation system according to claim 9, characterized in that: The topological constraints are generated according to the following steps; Determine the topology constraints for each business scenario, and define the required topology output for each business scenario; The topology constraints are derived based on the business requirements of each business scenario. Rules are formed using the topological constraints of each business scenario. The rules include: rule ID, business scenario name, topological constraints, and effective status field. When the effective status field is enabled, the rule is effective.

11. A business-driven distribution network panoramic dynamic topology atomic-level service implementation system according to claim 8, characterized in that: The graph database is mapped from a relational database, which stores equipment ledgers and equipment connection relationship tables.

12. The system for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven principles, as described in claim 11, is characterized in that: The graph database is mapped from a relational database and specifically includes: Using the unique device identifier as the core, define the mapping relationship between relational database fields and graph database attributes; By reading the equipment ledger and connection relationship table of the relational database, and using the defined mapping relationship between relational database fields and graph database attributes, the relational database fields are associated with the graph database attributes.

13. The system for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven principles, as described in claim 12, is characterized in that: When the graph database attributes are updated, the corresponding fields in the relational database are updated synchronously.

14. The system for implementing atomic-level services of a panoramic dynamic topology of a distribution network based on business-driven principles, as described in claim 12, is characterized in that: After associating relational database fields with graph database attributes, integrity and consistency checks are performed on the associated graph database. Only when both integrity and consistency checks pass can the graph database be obtained for use.

15. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which is then executed by the at least one processor to enable the at least one processor to perform the business-driven distribution network panoramic dynamic topology atomic-level service implementation method according to any one of claims 1-7.

16. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the atomic-level service implementation method for the panoramic dynamic topology of the power distribution network based on any one of claims 1-7.

17. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the business-driven atomic-level service implementation method for the dynamic topology of the distribution network panorama as described in any one of claims 1-7.

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