DTU Point Table Configuration and Parsing Method Based on Template Compression and Topology Partitioning

Abstract

This invention provides a DTU point table configuration and parsing method based on template compression and topology partitioning, relating to the field of distribution network automation technology. The method includes the following steps: collecting complete point table data for multiple typical DTUs, extracting common fields shared by all point tables, constructing a basic template and storing it in the master station template library and a subset of local templates for the DTU; dividing the distribution network into multiple logically independent sub-regions based on the physical structure of the distribution network, and assigning a unique topology identifier to each sub-region; this invention fundamentally solves the core pain point of repetitive configuration on a per-unit basis in traditional DTU configuration through a collaborative mechanism of general templates and topology partitioning. The construction of the basic template enables unified reuse of common parameters. Parameters that do not require differentiated adjustment, such as basic communication protocols, data acquisition cycles, or general control logic, do not need to be configured separately on each DTU; batch loading of common parameters can be completed directly through template calls.

Description

Technical Field

[0001] This invention relates to the field of distribution network automation technology, and in particular to a method for configuring and parsing DTU point tables based on template compression and topology partitioning. Background Technology

[0002] In distribution network automation systems, the Data Transfer Unit (DTU), as a key terminal device, needs to be configured via point tables to achieve data acquisition, communication interaction, and control logic execution. Current technologies for DTU point table configuration and parsing have the following shortcomings:

[0003] First, batch configuration is extremely inefficient. Existing methods require repeatedly setting common parameters for each DTU, and even DTUs of the same type and in the same partition cannot reuse configuration logic. For example, if a city's distribution network contains 500 DTUs of the same model, traditional configuration one by one would take 8-10 hours, resulting in a large amount of repetitive operations for maintenance personnel and making configuration errors prone to human error.

[0004] Secondly, the point table storage suffers from redundancy and poor compatibility. The DTU point table contains numerous duplicate fields, and storing the point table for each DTU completely wastes storage resources. Furthermore, the point table parsing algorithms of different manufacturers are specialized, requiring redevelopment of the parsing program when switching manufacturers, resulting in insufficient compatibility and increased system upgrade costs. In addition, DTU function upgrades require modifying the point table configuration for each unit, and changes in the topology necessitate re-selecting devices, leading to a disconnect between configuration logic and the power grid's physical structure, further reducing operational efficiency.

[0005] Therefore, this invention proposes a DTU point table configuration and parsing method based on template compression and topology partitioning to solve the problems existing in the prior art. Summary of the Invention

[0006] To address the aforementioned issues, this invention proposes a DTU point table configuration and parsing method based on template compression and topology partitioning. This method fundamentally solves the core pain point of repetitive configuration on a per-unit basis in traditional DTU configuration through a collaborative mechanism of general templates and topology partitioning. Specifically, the construction of the basic template enables the unified reuse of common parameters. Parameters that do not require differentiated adjustments, such as the device's basic communication protocol, data acquisition cycle, or general control logic, do not need to be configured separately on each DTU. Batch loading of common parameters can be completed directly through template calls.

[0007] To achieve the objectives of this invention, the invention is implemented through the following technical solution: a DTU point table configuration and parsing method based on template compression and topology partitioning, comprising the following steps:

[0008] S1: Collect complete point table data for multiple typical DTUs, extract common fields shared by all point tables, build a basic template and store it in the main site template library and a subset of local DTU templates;

[0009] S2: Based on the physical structure of the distribution network, the distribution network is divided into multiple logically independent sub-regions, and a unique topology identifier is assigned to each sub-region.

[0010] S3: The main station determines the sub-region to which the target DTU belongs, calls the basic template corresponding to that region, collects the differential parameters of the target DTU and fills them into the basic template, and generates a compression point table;

[0011] S4: The main station locates the basic template based on the topology identifier code of the target DTU and sends the compressed point table to the target DTU;

[0012] S5: The target DTU receives the compressed point table and its own topology identifier, calls the local matching basic template, merges the differentiated parameters in the compressed point table with the common fields of the basic template, and restores and generates a complete point table;

[0013] S6: DTU performs data validation on the complete point table. If the validation passes, the business logic corresponding to the point table is executed. If the validation fails, the main site is notified to resend the data.

[0014] A further improvement is made in S1, where the extraction of common fields from the basic template meets the extraction rate requirement, and the extraction rate is calculated using the following formula:

[0015]

[0016] Where: R is the common field extraction rate, in %, satisfying R≥80%; Cp is the number of extracted common fields, in units of, including device ID, communication address, and data acquisition cycle; Ct is the total number of fields in a single DTU point table, in units of,.

[0017] A further improvement is made in S2, where topology partitioning requires calculating partition granularity and defining topology identifier encoding rules, specifically including the partition granularity calculation formula:

[0018]

[0019] Where: G is the average number of DTUs in a single sub-region, in units, satisfying 10≤G≤50; Ndtu is the total number of DTUs in the distribution network, in units; K is the total number of sub-regions, in units;

[0020] Topology identifier encoding rules:

[0021] ID=Z m +M n +S p

[0022] Where: ID is the topology identifier (string); Z m For m-bit region encoding, m≥2; M n For n-bit feeder encoding, n≥3; S p Let p be the encoding of the station area, where p ≥ 3 and m + n + p ≥ 8.

[0023] A further improvement is made in S3, where the compression ratio of the compression point table meets the storage optimization requirements, and the compression ratio calculation formula is:

[0024]

[0025] Where: CR is the compression ratio of the compressed point table, in %, satisfying CR≥60%; D is the data volume of the differential parameters of a single DTU, in bytes, including device model, sampling accuracy, and alarm threshold; T is the data volume of the complete point table of a single DTU, in bytes.

[0026] The further improvement lies in the fact that, in S4, the main station configuration efficiency meets the improvement requirements, and the efficiency calculation formula is:

[0027]

[0028] Where: E represents the configuration efficiency improvement rate, in %, satisfying E≥50%; T trad Total time for configuring all DTUs in K sub-regions on a per-unit basis, in minutes; T new Total time for configuring the same number of DTUs for this method, in minutes.

[0029] A further improvement is made in the following: In step S4, the master station uses an encryption algorithm to process the compressed point table before sending it out; in step S5, the DTU uses a corresponding decryption algorithm after receiving the table. The encryption / decryption algorithms satisfy the following:

[0030] E key (D data )=C data

[0031] D key (C data )=D data

[0032] Where: E key (·) is the encryption function; D key (·) represents the decryption function; key is the symmetric encryption key, with a length ≥ 128 bits; D data This is the original compressed point table data, in bytes; C data The data is compressed into an encrypted point table, in bytes, and the encryption algorithm is selected from either AES-128 or SM4.

[0033] A further improvement is made in S5, where the CPU resource consumption during DTU parsing meets the optimization requirements, and the formula for calculating the CPU utilization reduction rate is:

[0034]

[0035] Where: C is the CPU utilization reduction rate, in %, and must satisfy C≥50%; trad This represents the average CPU utilization during DTU's traditional parsing of complete point tables, in %; C. new The average CPU utilization rate when DTU parses the compressed point table using this method is expressed in percent.

[0036] A further improvement is made in S5, where the compatibility of multi-vendor DTUs meets the adaptation requirements, and the formula for calculating the matching success rate is:

[0037]

[0038] Where: S is the manufacturer's DTU adaptation success rate, in %, satisfying S≥95%; N succ The number of DTUs from different manufacturers that have been successfully adapted, in units of: units; N total The total number of DTUs from different manufacturers participating in the test, in units of, and N total ≥3.

[0039] A further improvement is made in S6, where the accuracy of the point table parsing meets the reliability requirements, and the accuracy calculation formula is:

[0040]

[0041] Where: A represents the accuracy of the point table analysis, in percentage (%), satisfying A≥99.5%; N err Total number of fields in the parsed point table that have errors, in units of: N total_tbl The total number of field values ​​in the point table for all test DTUs, in units of numbers, and N total_tbl =N test ×C t N test To test the number of DTUs, C t This represents the total number of fields in the table for a single DTU.

[0042] Further improvements include a dynamic topology adjustment step, with the adjustment time meeting scalability requirements. The time calculation formula is as follows:

[0043] T adj =T add +T merge +T del

[0044] And T adj ≤30%×T trad_adj

[0045] Wherein: T adj Total time for dynamic topology adjustment, unit: minutes; T add The time taken to add a new sub-region, in minutes; T merge The time taken to merge existing sub-regions, in minutes; T del Time taken to delete invalid sub-regions, in minutes; T trad_adj Total time for adjusting a traditional topology: re-screening devices + full configuration, in minutes.

[0046] The beneficial effects of this invention are as follows:

[0047] 1. This invention fundamentally solves the core pain point of repetitive configuration of each DTU in traditional DTU configuration by using a collaborative mechanism of universal templates and topology partitioning. The construction of basic templates enables unified reuse of common parameters. Parameters that do not require differentiated adjustment, such as basic communication protocols, data acquisition cycles, and general control logic, do not need to be configured individually on each DTU; they can be batch-loaded directly through template calls. Topology partitioning divides a large number of DTUs into logically independent sub-regions based on the distribution network's physical structure. Maintenance personnel do not need to screen devices one by one during configuration; they only need to quickly locate the corresponding template based on the topology partition to which the target DTU belongs to complete the basic configuration framework for all DTUs of the same type within that partition. This configuration mode not only simplifies the operation process but also avoids repetitive work caused by manual configuration of each DTU. Especially in scenarios with large distribution networks and a large number of DTUs, it transforms the configuration process from single-point operation to batch coverage, significantly improving overall configuration efficiency and reducing human configuration errors caused by repetitive operations, further ensuring the consistency of configuration results.

[0048] 2. This invention uses template compression technology to split the point table data into two parts: a basic template and differentiated parameters. The basic template is stored as common data in the master station template library and a subset of local templates in the DTU, requiring only a one-time deployment for reuse by multiple DTUs. The differentiated parameters contain only personalized configuration information unique to each DTU, with a data volume far smaller than the complete point table. This storage mode not only greatly reduces the local storage occupation of the DTU and avoids the waste of storage resources due to duplicate fields, but also significantly reduces network bandwidth consumption during data transmission, reduces transmission latency, and improves the real-time performance of data interaction, especially in scenarios with complex distribution network environments and limited bandwidth, effectively ensuring the efficient transmission of configuration data.

[0049] 3. This invention standardizes the common parameter parsing logic through a universal basic template. Regardless of the manufacturer of the DTU, the parsing rules for common parameters are executed based on a unified template, eliminating the need to design separate parsing logic for different manufacturers. For the differentiated needs of DTUs from different manufacturers, adaptation can be achieved simply by adjusting the matching rules for the differentiated parameters. For example, to address the differences between DTUs from different manufacturers in terms of sampling accuracy units, alarm triggering logic, etc., compatibility can be achieved through lightweight operations such as modifying parameter mapping relationships and format conversion rules, without the need to develop entirely new parsing algorithms. This compatibility mode significantly reduces the system's dependence on specific manufacturer equipment. When adding manufacturer equipment or replacing existing equipment, there is no need to reconstruct the entire parsing and configuration system, effectively shortening the adaptation cycle, reducing development and expansion costs, and ensuring the overall stability and compatibility of the system.

[0050] 4. In this invention, the differentiated parameters and the basic template are independent of each other. If only the differentiated parameters are damaged or incorrect, it is not necessary to reissue the complete point table. Only the differentiated parameters need to be repaired or reissued to restore the parsing function, which greatly improves the reliability and fault tolerance of the parsing process and reduces the overall failure caused by local problems. In addition, the topology partitioning design deeply binds the DTU point table configuration with the distribution network physical structure. The topology identification code of the DTU directly reflects its physical location and belonging relationship in the power grid. This point table-topology integrated structure enables the DTU to automatically match the corresponding configuration template through the topology identification code when it is connected to the distribution network. Initialization configuration can be completed without manual intervention, providing core support for the plug-and-play function of the distribution network DTU. At the same time, the point table data based on topology partitioning can be linked with the power grid model, providing accurate equipment location and configuration data support for subsequent advanced applications such as automatic distribution network topology derivation, fault location and isolation, and intelligent operation and maintenance, promoting the upgrade of distribution network automation to intelligence.

[0051] 5. In this invention, when the DTU model is upgraded or its function is iterated, only the basic templates in the master station template library and the local template subset of the DTU need to be updated. There is no need to modify the point table configuration of each DTU individually. For example, the common parameter fields required for the new function can be directly integrated into the basic template. All associated DTUs can obtain the new function configuration by calling the updated template, which greatly shortens the upgrade cycle and reduces the maintenance workload. When adjusting the distribution network topology, whether adding a topology partition, merging an existing partition, or deleting an invalid partition, there is no need to re-screen all devices. Only the mapping relationship between the partition division and the topology identifier code needs to be adjusted in the master station system to quickly complete the configuration adaptation. This avoids the complex process of re-screening devices and full configuration in traditional topology adjustments, reducing the complexity and time cost of maintenance operations. This efficient upgrade and adjustment mode enables the system to flexibly adapt to scenarios such as the expansion of the distribution network scale, equipment updates, and topology changes, without the need to reconstruct the overall configuration and resolution system, which significantly improves the scalability and long-term operation and maintenance economy of the system. Attached Figure Description

[0052] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0053] To enhance understanding of the present invention, the present invention will be further described in detail below with reference to embodiments. These embodiments are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0054] Example 1

[0055] according to Figure 1 As shown, this embodiment proposes a DTU point table configuration and parsing method based on template compression and topology partitioning, for batch initial configuration of DTUs at the feeder level in urban distribution networks:

[0056] Application scenario: The third feeder in the western part of a prefecture-level city is responsible for power supply to 12 residential communities. It is necessary to complete the initial point table configuration for the 35 newly added DTUs of the same model (model: DTU-2024A) on this feeder. The configuration content includes parameters such as communication address, data acquisition cycle, and basic alarm logic.

[0057] Implementation steps:

[0058] Template Construction: Collect complete point table data for DTU-2024A model. A single point table contains 55 fields (such as device ID, communication port, sampling interval, voltage acquisition range, etc.). Extract 46 common fields (common fields account for 83.6%). These common fields are the common configurations for all 35 DTUs (such as communication protocol uniformly set to IEC104, sampling interval uniformly set to 5 seconds, and voltage acquisition range uniformly set to 0-12kV). Based on these common fields, construct a "feeder-level DTU basic template" and store it synchronously in the main station template library and the local template subset of the 35 DTUs.

[0059] Topology partitioning: Based on the physical structure of the distribution network, the third feeder in the western city area is divided into an independent topology sub-area, and a unique topology identifier code "02+003+000" is assigned to this area (where "02" represents the western city area, "003" represents the third feeder, and "000" represents the feeder-level general identifier), ensuring that the master station and DTU can quickly match templates through this identifier code.

[0060] Compressed Point Table Generation: Collect differentiated parameters from 35 DTUs. Each DTU's differentiated parameters contain only 5 unique serial numbers (such as device numbers "DTU-02-003-001" to "DTU-02-003-035") and 2 personalized alarm thresholds (such as overvoltage alarm values ​​set to 10.5kV or 10.8kV according to the differences in cell load). The data volume of a single differentiated parameter is only 112 bytes, while the data volume of the complete point table is 304 bytes. The compressed data volume is only 36.8% of that of the complete point table.

[0061] Configuration distribution and parsing: The main station locates the "feeder-level DTU basic template" in the template library through the topology identifier code "02003000" and distributes the compressed point table of 35 DTUs in batches with encryption; after each DTU receives the configuration, it calls the locally stored basic template, fills the differentiated parameters into the corresponding fields of the template, restores the complete point table, and then automatically verifies the integrity of the parameters.

[0062] Validation data:

[0063] Configuration time comparison: The traditional method requires logging into the DTU one by one for configuration, with an average time of 2 minutes per unit, and a total time of 70 minutes for 35 units; the method of this invention only requires building a template (10 minutes), collecting differentiated parameters (5 minutes), and batch distribution (9 minutes), with a total time of 24 minutes, reducing the time by 65.7%.

[0064] Configuration error rate comparison: Traditional one-by-one configuration resulted in 4 configuration errors on 35 DTUs due to human input errors (error rate 11.4%); the method of this invention, through unified template reuse and automatic parameter filling, resulted in no configuration errors on any of the 35 units (error rate 0%).

[0065] Example 2

[0066] according to Figure 1 As shown, this embodiment proposes a DTU point table configuration and parsing method based on template compression and topology partitioning, and provides compatibility analysis for multi-vendor DTU hybrid deployment:

[0067] Application scenario: A power distribution network in an industrial park needs to connect to 5 DTUs from different manufacturers (namely, DTU500 from manufacturer A, ZT-DTU from manufacturer B, PN-DTU from manufacturer C, XJ-DTU from manufacturer D, and NS-DTU from manufacturer E), with 25 units from each manufacturer, for a total of 125 DTUs. It is necessary to achieve unified resolution of the point table for all DTUs to avoid resolution failures caused by differences in manufacturers.

[0068] Implementation steps:

[0069] General template construction: Data points of DTUs from 5 manufacturers were collected, and it was found that all manufacturers' data points contained 48 common fields (such as device IP address, data upload port, number of current acquisition channels, remote signaling status definition, etc.). Based on these common fields, a "general DTU template for industrial parks" was constructed to ensure that the template can cover the basic parsing requirements of all manufacturers.

[0070] Manufacturer-specific adaptation: For each manufacturer's unique point table rules (such as alarm codes of manufacturer A being in hexadecimal, sampling precision of manufacturer B retaining 3 decimal places, and remote signaling status "1" representing tripping of manufacturer C), only the matching rules of the differentiated parameters are adjusted (such as setting a "manufacturer identifier-parameter format" mapping table on the main station, and storing the corresponding format conversion logic locally on the DTU), without modifying the core parsing logic of the general template.

[0071] Batch parsing test: The main station assigns corresponding topology identification codes to 125 DTUs (e.g., the identification code of the first DTU of Manufacturer A is "03+001+001", where "03" represents the industrial park, "001" represents the region of Manufacturer A, and "001" represents the equipment serial number), and sends out a compressed point table containing manufacturer-specific parameters; after receiving the table, the DTU calls the general template through the topology identification code and parses the parameters by combining the local format conversion logic.

[0072] Validation data:

[0073] Manufacturer compatibility success rate: Out of 125 DTUs, only 2 DTUs from vendor E failed to resolve on the first attempt due to incorrect initial parameter format (they succeeded after re-issuing differentiated parameters), resulting in 123 successful resolutions, with a success rate of 98.4%. The traditional method requires developing 5 dedicated resolution programs for 5 vendors, and the success rate is only 82% (due to resolution failure caused by vendor parameter updates).

[0074] Parsing accuracy: A sample of the point table fields of 125 DTUs was checked (20 fields were sampled from each DTU, for a total of 2500 fields). Only 3 fields were found to have parsing errors due to packet loss during transmission, with a parsing accuracy of 99.88%. The traditional method had 47 parsing errors in 2500 fields due to compatibility issues with the vendor's proprietary program, with an accuracy of only 98.12%.

[0075] Parsing time: The average time for a single DTU to parse a compressed point table is 0.8 seconds; the average time for parsing a complete point table using the traditional method is 2.3 seconds, resulting in a 65.2% improvement in parsing speed.

[0076] Example 3

[0077] according to Figure 1 As shown, this embodiment proposes a DTU point table configuration and parsing method based on template compression and topology partitioning, enabling rapid template updates during DTU function upgrades:

[0078] Application scenario: A distribution network in a certain urban area has deployed 120 DTUs (model: DTU-2023B). Due to the need for intelligent distribution network, it is necessary to add "fault recording function" to all DTUs. This function requires adding three fields to the point table: "recording duration", "recording trigger current threshold" and "recording data storage path". The traditional method requires modifying the point table for each DTU, which is time-consuming.

[0079] Implementation steps:

[0080] Template update: Locate the "Urban DTU Basic Template" in the main site template library (the original template contains 52 fields), and directly add 3 common fields related to fault recording (the recording duration is 5 seconds by default, the trigger current threshold is 120A by default, and the storage path is " / data / recorder" by default). The template update takes only 3 minutes and does not require modification of any existing differentiated parameters of the DTU (such as device number and personalized alarm value).

[0081] Template distribution: The main station distributes the updated basic template to 120 DTUs in batches using the topology identifier code "01+001-010+000" ("01" represents the urban area, and "001-010" represents 10 urban feeder sub-sections). Each DTU automatically replaces the old local template after receiving it, without the need for manual intervention.

[0082] Function verification: After the distribution is completed, the main station sends a "fault recording test command" to 120 DTUs. All DTUs can generate recording data that meets the requirements based on the updated template parsing command, and the function activation success rate is 100%.

[0083] Validation data:

[0084] Upgrade time: The total upgrade time of this invention is only 15 minutes (3 minutes for template update + 12 minutes for batch distribution); the traditional method requires logging into DTU to modify the point table for each machine, with an average time of 50 seconds per machine, and a total time of 100 minutes for 120 machines, thus improving upgrade efficiency by 85%.

[0085] Upgrade cost: Traditional methods require two maintenance personnel to operate on-site (some DTUs require on-site debugging), with labor costs of approximately 1200 yuan; the method of this invention only requires one maintenance personnel to complete the operation at the main station, reducing labor costs by 50%, and does not require interruption of normal DTU operation (traditional methods require pausing data acquisition for approximately 2 minutes during each DTU debugging, with a total interruption time of 240 minutes).

[0086] Example 4

[0087] according to Figure 1 As shown, this embodiment proposes a DTU point table configuration and parsing method based on template compression and topology partitioning for batch configuration of DTUs in large-scale county-level distribution areas:

[0088] Application scenario: A distribution network in a county-level city covers 20 townships and needs to be configured for 500 DTUs (divided into 10 topology partitions, with 50 units in each partition, corresponding to 50 distribution areas). The configuration content includes parameters such as distribution area user number, three-phase voltage acquisition, and power factor calculation. All configurations must be completed within 1.5 hours. Traditional configuration one unit at a time cannot meet the time requirement.

[0089] Implementation steps:

[0090] Partitioning and Template Construction: Based on the county-level distribution network single-line diagram, the 20 townships are divided into 10 topology partitions (each partition consists of 2 townships). Each partition is assigned an identifier code (e.g., "04+001+000" represents the first partition, "04" represents the county-level city, and "001" represents the partition number). For the common requirements of DTUs in the distribution area (e.g., voltage acquisition range of 0-400V, power factor calculation cycle of 1 minute), a "Distribution Area DTU Basic Template" is constructed, with each template containing 45 common fields.

[0091] Differentiated parameter acquisition: Collect parameters unique to each of the 50 DTUs in each zone (such as zone number "TQ-04-001-001" to "TQ-04-001-050", number of users in the zone, and transformer capacity). The data size of each differentiated parameter is 96 bytes, and the data size of the complete point table is 288 bytes. After compression, the data size is reduced by 66.7%.

[0092] Batch configuration: The master station distributes the compression point table sequentially by partition. Each partition of 50 DTUs only needs to be configured with one command. During the distribution process, the master station automatically matches the basic template of the corresponding partition through the topology identifier code, without the need for manual selection of devices.

[0093] Validation data:

[0094] Configuration timeliness: The method of this invention takes a total of 85 minutes from template construction (20 minutes), parameter collection (30 minutes), and batch distribution (35 minutes), completing the configuration of all 500 DTUs within 1.5 hours (90 minutes); the traditional method requires 1.2 minutes to configure each unit, and the total time for 500 units is 600 minutes, which far exceeds the timeliness requirement.

[0095] Resource consumption: Each DTU requires 288 bytes of local storage for the complete point table, and 500 units require a total storage of 144,000 bytes. In the method of this invention, each DTU only stores the basic template (144 bytes) + differentiated parameters (96 bytes), with a total storage of 120,000 bytes, reducing storage resources by 16.7%. At the same time, the average CPU utilization rate when the DTU parses the compressed point table is 16%, while the average CPU utilization rate when parsing the complete point table in the traditional method is 40%, reducing CPU resource consumption by 60%.

[0096] Example 5

[0097] according to Figure 1 As shown, this embodiment proposes a DTU point table configuration and parsing method based on template compression and topology partitioning, enabling rapid adaptation to distribution network topology adjustments and the addition of new feeders:

[0098] Application scenario: A new urban area plans to add a 10kV feeder (responsible for power supply to 8 newly built residential areas). It is necessary to configure 28 DTUs for the feeder and complete the configuration and connection to the distribution network system within 2 hours. The traditional method requires re-screening the entire list of distribution network equipment, which takes a long time.

[0099] Implementation steps:

[0100] Adding a new topology partition: In the main station topology management module, add a sub-region "New City Area Feeder No. 8" and assign a topology identifier code "05+008+000" ("05" represents New City Area and "008" represents Feeder No. 8). The operation of adding a partition only requires filling in the area name, feeder number and coverage area in the system, which takes 2 minutes.

[0101] Template reuse: Since the newly added DTU model (DTU-2024A) is the same as the existing urban feeder DTU model, the "urban feeder DTU basic template" can be reused directly without rebuilding the template. Only the differentiated parameters of 28 DTUs (such as equipment installation location and cell number) need to be collected, which takes 4 minutes.

[0102] Configuration and Access: The master station uses the topology identifier code "05008000" of the new partition to locate the template and distributes the compressed point table of 28 DTUs in batches (takes 5 minutes); after the DTUs are parsed, they automatically send an "access request" to the master station. The master station verifies the device ownership based on the topology identifier code and completes the access. The entire access process does not require manual verification of device information.

[0103] Validation data:

[0104] Adjustment time: The method of this invention takes a total of 16 minutes from topology addition (2 minutes), parameter collection (4 minutes), configuration distribution (5 minutes), and device access (5 minutes); the traditional method requires re-exporting the full list of distribution network devices (15 minutes), filtering and adding feeder devices (20 minutes), configuring each device (56 minutes), and manual verification of access (30 minutes), with a total time of 121 minutes, improving the adjustment efficiency by 86.8%.

[0105] Access stability: After the 28 newly added DTUs were connected, the data upload success rate was 99.92% during a continuous 72-hour test, with no offline or data loss due to configuration issues; the data upload success rate of devices configured using traditional methods was 98.7% during the same test period, with 3 DTUs experiencing offline twice due to human configuration errors.

[0106] This invention fundamentally solves the core pain point of repetitive configuration of each DTU in traditional DTU configuration by using a collaborative mechanism of universal templates and topology partitioning. The construction of the basic template enables unified reuse of common parameters. Parameters that do not require differentiated adjustment, such as basic communication protocols, data acquisition cycles, and general control logic, do not need to be configured individually on each DTU; they can be batch-loaded directly through template calls. Topology partitioning divides a large number of DTUs into logically independent sub-regions based on the distribution network's physical structure. Maintenance personnel do not need to screen devices one by one during configuration; they only need to quickly locate the corresponding template based on the topology partition to which the target DTU belongs to complete the basic configuration framework for all DTUs of the same type within that partition. This configuration mode not only simplifies the operation process but also avoids repetitive work caused by manual configuration of each DTU. Especially in scenarios with large distribution networks and a large number of DTUs, it transforms the configuration process from single-point operation to batch coverage, significantly improving overall configuration efficiency and reducing human configuration errors caused by repetitive operations, further ensuring the consistency of configuration results. This invention utilizes template compression technology to split point table data into two parts: a basic template and differentiated parameters. The basic template, as common data, is uniformly stored in the master station template library and a subset of local templates on the DTU, requiring only a one-time deployment for reuse by multiple DTUs. The differentiated parameters contain only personalized configuration information unique to each DTU, with a data volume far smaller than the complete point table. This storage mode not only significantly reduces the local storage footprint of the DTU and avoids the waste of storage resources due to duplicate fields, but also, when the master station sends configuration data to the DTU, only the smaller differentiated parameters need to be transmitted, greatly reducing network bandwidth consumption during data transmission, reducing transmission latency, and improving the real-time performance of data interaction. Especially in scenarios with complex distribution network environments and limited bandwidth, it can effectively ensure the efficient transmission of configuration data. This invention standardizes the parsing logic of common parameters through a universal basic template. Regardless of the manufacturer of the DTU, the parsing rules for common parameters are executed based on a unified template, eliminating the need to design separate parsing logic for different manufacturers. For the differentiated needs of DTUs from different manufacturers, adaptation can be achieved simply by adjusting the matching rules for the differentiated parameters. For example, to address the differences between DTUs from different manufacturers in terms of sampling precision units, alarm triggering logic, etc., compatibility can be achieved through lightweight operations such as modifying parameter mapping relationships and format conversion rules, without the need to develop entirely new parsing algorithms. This compatibility mode significantly reduces the system's dependence on specific manufacturer equipment. When adding manufacturer equipment or replacing existing equipment, there is no need to reconstruct the entire parsing and configuration system, effectively shortening the adaptation cycle, reducing development and expansion costs, and ensuring the overall stability and compatibility of the system.In this invention, the differentiated parameters and the basic template are independent of each other. If only the differentiated parameters are damaged or erroneous, it is not necessary to reissue the complete point table. Only the differentiated parameters need to be repaired or reissued to restore the parsing function, which greatly improves the reliability and fault tolerance of the parsing process and reduces overall failures caused by local problems. In addition, the topology partitioning design deeply binds the DTU point table configuration with the distribution network physical structure. The topology identifier code of the DTU directly reflects its physical location and belonging relationship in the power grid. This point table-topology integrated structure enables the DTU to automatically match the corresponding configuration template through the topology identifier code when it is connected to the distribution network. Initialization configuration can be completed without manual intervention, providing core support for the plug-and-play function of the distribution network DTU. At the same time, the point table data based on topology partitioning can be linked with the power grid model, providing accurate equipment location and configuration data support for subsequent advanced applications such as automatic distribution network topology derivation, fault location and isolation, and intelligent operation and maintenance, promoting the upgrade of distribution network automation to intelligence. In this invention, when a DTU model is upgraded or its function is iterated, only the basic templates in the master station template library and the DTU local template subset need to be updated. There is no need to modify the point table configuration of each DTU individually. For example, common parameter fields required for new functions can be directly integrated into the basic template. All associated DTUs can obtain the new function configuration by calling the updated template, which greatly shortens the upgrade cycle and reduces the maintenance workload. When adjusting the distribution network topology, whether adding a topology partition, merging an existing partition, or deleting an invalid partition, there is no need to re-screen all devices. Only the mapping relationship between partition division and topology identifier code needs to be adjusted in the master station system to quickly complete the configuration adaptation. This avoids the complex process of re-screening devices and full configuration in traditional topology adjustments, reducing the complexity and time cost of maintenance operations. This efficient upgrade and adjustment mode enables the system to flexibly adapt to scenarios such as the expansion of distribution network scale, equipment updates, and topology changes without reconstructing the overall configuration and resolution system, which significantly improves the scalability and long-term operation and maintenance economy of the system.

[0107] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for DTU point table configuration and parsing based on template compression and topological partitioning, characterized in that, The method comprises the following steps: S1: Collecting complete point table data of multiple typical DTUs, extracting common fields shared by all point tables, constructing a basic template and storing it in a master station template library and a DTU local template subset; S2: Dividing the distribution network into multiple logically independent sub-regions based on the physical structure of the distribution network, and assigning a unique topological identification code to each sub-region; S3: The master station determines the sub-region to which the target DTU belongs, calls the basic template corresponding to the region, collects the differential parameters of the target DTU and fills them into the basic template to generate a compressed point table; S4: The master station locates the basic template based on the topological identification code of the target DTU and downloads the compressed point table to the target DTU; S5: The target DTU receives the compressed point table and its topological identification code, calls the locally matched basic template, fuses the differential parameters in the compressed point table with the common fields of the basic template, and restores the complete point table; S6: The DTU performs data verification on the complete point table, and if the verification is passed, executes the business logic corresponding to the point table, and if the verification fails, feeds back to the master station to request re-download.

2. The method of claim 1, wherein the method further comprises: In the S1, the common fields of the basic template meet the extraction rate requirement, and the extraction rate calculation formula is: ， Wherein: R is the common field extraction rate, unit: %, meets R≥80%; Cp is the number of extracted common fields, unit: pieces, the common fields include device ID, communication address and data acquisition period; Ct is the total number of fields of a single DTU point table, unit: pieces.

3. The method of claim 1, wherein the method further comprises: determining a template compression and topology partitioning based DTU point table configuration and parsing method. In the S2, the topological partition needs to calculate the partition granularity and define the topological identification code coding rule, specifically including, the partition granularity calculation formula: ， Wherein: G is the average number of DTUs in a single sub-region, unit: units, meets 10≤G≤50; Ndtu is the total number of DTUs in the distribution network, unit: units; K is the total number of sub-regions, unit: pieces; The topological identification code coding rule is: ， ID is a topology identification code; m is a region code, m≥2; n is a feeder code, n≥3; p is a cell code, p≥3, and m+n+p≥8.

4. The method of claim 1, wherein the method further comprises: determining a template compression and topology partitioning based DTU point table configuration and parsing method. In the S3, the compression rate of the compressed point table meets the storage optimization requirement, and the compression rate calculation formula is: ， Wherein: CR is the compression rate of the compressed point table, unit: %, meets CR≥60%; D is the data volume of the differential parameters of a single DTU, unit: bytes, the differential parameters include device model, sampling accuracy and alarm threshold; T is the data volume of the complete point table of a single DTU, unit: bytes.

5. The method of claim 1, wherein: In the S4, the master station configuration efficiency meets the improvement requirement, and the efficiency calculation formula is: ， Wherein: E is the configuration efficiency improvement rate, unit: %, satisfies E≥50%; T is the total time of configuring K sub-regions of all DTUs in traditional per station, unit: minutes; T is the total time of configuring the same number of DTUs by the method, unit: minutes.

6. The method of claim 5, wherein: In the S4, the master station uses an encryption algorithm before downloading the compressed point table, and the DTU uses a corresponding decryption algorithm after receiving, and the encryption / decryption algorithm meets: ， Wherein: is an encryption function; is a decryption function; key is a symmetric encryption key, length >= 128 bits; is the original compressed point table data, unit: byte; is the encrypted compressed point table data, unit: byte, and the encryption algorithm is selected from any one of AES-128 and SM4.

7. The method of claim 1, wherein: In the S5, the CPU resource consumption of the DTU during analysis meets the optimization requirement, and the CPU occupancy rate reduction rate calculation formula is: ， Wherein: C is the CPU occupancy reduction rate, unit: %, need to meet C≥50%; is the CPU average occupancy rate when the DTU traditionally parses the complete point table, unit: %; is the CPU average occupancy rate when the DTU parses the compressed point table through the method, unit: %.

8. The method of claim 1, wherein: In the S5, the compatibility of multiple manufacturer DTUs meets the adaptation requirement, and the matching success rate calculation formula is: ， Wherein: S is the success rate of manufacturer DTU adaptation, unit: %, and S≥95% is met; is the number of different manufacturer DTUs that are adapted successfully, unit: pieces; is the total number of different manufacturer DTUs participating in the test, unit: pieces, and ≥3.

9. The method of claim 1, wherein: In the S6, the point table analysis accuracy meets the reliability requirement, and the accuracy calculation formula is: ， Wherein: A is the point table analysis accuracy, unit: %, A≥99.5%; is the total number of point table fields of the analysis error, unit: pieces; is the total number of point table fields of all test DTUs, unit: pieces, and , is the number of test DTUs, is the total number of point table fields of a single DTU.

10. The method of claim 1, wherein: Further comprising a topological dynamic adjustment step, and the adjustment time consumption meets the expansibility requirement, and the time consumption calculation formula is: ， and , Wherein: is the total consumption time of topology dynamic adjustment, unit: minutes; is the consumption time of adding a sub-area, unit: minutes; is the consumption time of merging an existing sub-area, unit: minutes; is the consumption time of deleting an invalid sub-area, unit: minutes; is the total consumption time of traditional topology adjustment: re-screening equipment + full configuration, unit: minutes.

Images