Marketing and distribution data-based line loss verification and evaluation method, apparatus and device, and medium

Abstract

The invention relates to the technical field of electric power monitoring, and discloses a line loss verification and evaluation method based on marketing and distribution data, which comprises the following steps: acquiring real-time data from a marketing and metering system according to a line loss target and a data threshold value, and performing synchronization, duplicate removal and verification to obtain preliminary cleaning data; after the format is unified, the user ID and the transformer number are associated and integrated into standard data, and the standard data are stored according to themes to obtain structured data. Checking inconsistent lists of the real-time topology tree and the in-book topology tree, and updating a marketing system; and analyzing a new energy data identification scene, switching a line loss model, and combining with an updating system to complete line loss verification. The invention also provides a line loss verification and evaluation device and equipment based on marketing and distribution data, and a storage medium. The intelligent level of line loss management and control can be improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric power monitoring, in particular to a line loss verification and evaluation method and device based on marketing and distribution data, equipment and medium. BACKGROUND

[0002] With the advancement of smart grid construction and the upgrading of electricity service demand, the requirement for data accuracy and intelligent level of management and control of distribution network line loss management is continuously improved. In traditional line loss management, data updating between distribution network automation system and marketing system relies on manual operation and electronic transfer, which has many problems: data lagging for a long time is common, human errors occur from time to time, which causes the line and transformer topology relationship in the marketing system to be unable to update in time, and the actual operation condition is seriously out of touch with the actual operation condition, which directly affects the accuracy of line loss calculation, and brings great challenges to the fine management of distribution network.

[0003] In recent years, distributed photovoltaic, charging load energy storage and other new energy are widely connected to the distribution network, and the intermittency and volatility of their output make the power flow distribution of the distribution network complex and changeable. The traditional line loss calculation method based on stable power supply and single power flow mode is no longer applicable, and it is unable to accurately reflect the real line loss of the distribution network after the connection of new energy, and it is difficult to meet the efficient and accurate line loss management and control requirements of modern distribution network. SUMMARY

[0004] The present application provides a line loss verification and evaluation method, device, equipment and medium based on marketing and distribution data, which mainly aims to improve the intelligent level of line loss management and control.

[0005] To achieve the above purpose, the present application provides a line loss verification and evaluation method based on marketing and distribution data, which comprises:

[0006] Based on the preset line loss management and control target and data quality threshold, the real-time running state data between the data source system cluster is obtained, wherein the data source system cluster comprises a marketing system and a metering automation system;

[0007] The real-time running state data between the data source system cluster is synchronized to obtain synchronized state data, and the synchronized state data is de-duplicated and format-verified to obtain preliminary cleaning state data;

[0008] Based on the preset format adjustment rule, the format of the preliminary cleaning state data is unified to obtain format normalized state data, and according to the marketing system and the metering automation system, the format normalized state data is integrated by using the preset user ID and transformer number to obtain standard unified state data;

[0009] acquire a data subject of the standard unified state data, and store the standard unified state data to a preset middle platform database based on the data subject, to obtain structured subject data;

[0010] acquire a keyword in the structured subject data, a real-time topology tree and a register topology tree, and check whether nodes of the real-time topology tree and the register topology tree are consistent with the keyword as a comparison core, to obtain an inconsistent information list;

[0011] send the inconsistent information list to a marketing system, perform topology updating according to a list type of the inconsistent information list, to obtain an updated marketing system, extract new energy operation library data in the structured subject data, analyze an association relationship between new energy processing and a power distribution network based on the new energy operation library data, acquire an identified application scenario, switch a line loss calculation model based on the identified application scenario, to obtain an adjusted line loss calculation model, and perform line loss checking and evaluation by using the adjusted line loss calculation model and the updated marketing system.

[0012] Optionally, the real-time operation state data between the data source system clusters is acquired based on a preset line loss control target and a data quality threshold, including:

[0013] acquire a standardized data interface of the data source system clusters, and configure data acquisition rules for each data source system in the data source system clusters based on the line loss control target and the data quality threshold, wherein the data acquisition rules include that a measurement automation system measures data at 15 minutes / once, a new energy data acquisition frequency is set to 5 minutes / once, a smart measurement terminal collects user-transformer association information at 15 minutes / once, and data is uploaded to the measurement automation system through a power wireless private network after being encrypted;

[0014] acquire state data by using the data acquisition rules based on the standardized data interface, to obtain initial state data, and perform format checking, integrity checking and timeliness checking on the initial state data, to obtain real-time operation state data, wherein the real-time operation state data includes dynamic topology, electrical measurement and static basic data.

[0015] Optionally, the real-time operation state data between the data source system clusters is synchronized to obtain synchronized state data, and the synchronized state data is de-duplicated and format-verified to obtain preliminary cleaned state data, including:

[0016] the time bases of each data source system in the data source clusters are unified through a preset clock synchronization protocol, data with an acquisition time difference exceeding a preset time threshold is removed, and the real-time operation state data is sorted according to an acquisition time stamp, to obtain sorted operation data;

[0017] Based on the preset user ID, transformer number, collection timestamp, a hash index is constructed, repeated records in the sorting running data are identified and removed through the hash index, the latest version of repeated data with version difference in the sorting running data is retained, and synchronization state data is obtained;

[0018] According to the preset JSON schema, the data format is verified, the fields in the synchronization state data that do not conform to the specification are converted or marked as abnormal, and the data records lacking key information are supplemented or removed, and a log file containing abnormal verification results is generated;

[0019] The data in the log file is reorganized according to the preset standard data structure, the data source identifier and the data quality score are supplemented, and preliminary cleaning state data is obtained.

[0020] Optionally, the format of the preliminary cleaning state data is unified based on the preset format adjustment rule to obtain format normalized state data, and the format normalized state data is integrated based on the marketing system and the metering automation system, using the preset user ID and transformer number, to obtain standard unified state data, including:

[0021] Based on the format adjustment rule, each system field in the preliminary cleaning state data is uniformly converted to obtain format normalized state data;

[0022] Based on the user ID and transformer number, the format normalized state data is adjusted to a topology structure to obtain topology structure data, and the integrated data of the topology structure data is packaged into a unified JSON format to obtain standard unified state data, wherein the format of the topology structure data is district-transformer-user-new energy.

[0023] Optionally, after the inconsistent node information is summarized to obtain an inconsistent information list, the method further includes:

[0024] The updated registered topology data of the marketing system is returned to the preset middle platform;

[0025] The inconsistent information list is classified according to problem types to generate a processing work order containing problem description, impact range, and priority;

[0026] Based on the processing work order, the marketing system triggers a correction process to obtain simple problems and complex problems in the processing work order, and processes them respectively to obtain a processing work order.

[0027] Optionally, the new energy operation library data in the structured theme data is extracted, a correlation between new energy processing and a power distribution network is analyzed based on the new energy operation library data, and an application scenario is identified, including:

[0028] New energy operation library data in structured theme data is collected, and the new energy operation data is encrypted and uploaded, and format, integrity, and timeliness verification is performed to obtain structured new energy operation data;

[0029] The fusion topology and load data in the structured new energy operation data are analyzed, and output fluctuation and voltage deviation, access capacity and carrying capacity are output, and a quantitative correlation between new energy processing and a preset power distribution network is mined to obtain a correlation identification result;

[0030] Based on the correlation identification result, typical application scenarios of power distribution network voltage regulation, consumption optimization, carrying capacity evaluation, and fault warning are identified to obtain an identified application scenario.

[0031] Optionally, the line loss verification and evaluation is performed using the adjusted line loss calculation model and the updated marketing system, including:

[0032] Based on the adjusted line loss calculation model and the updated marketing system, the line loss rate of each sub-district, the high-loss anomaly list and the optimization suggestions are output, and the line loss verification and evaluation are performed.

[0033] To solve the above problems, the application also provides a line loss verification and evaluation device based on marketing and distribution data, the device comprises:

[0034] A data acquisition module is configured to acquire real-time operation state data between data source system clusters based on a preset line loss control target and a data quality threshold, wherein the data source system clusters include a marketing system and a metering automation system;

[0035] A data processing module is configured to synchronize the real-time operation state data between the data source system clusters to obtain synchronized state data, and to perform de-duplication and format verification on the synchronized state data to obtain preliminary cleaned state data;

[0036] Based on a preset format adjustment rule, the format of the preliminary cleaned state data is unified to obtain format normalized state data, and based on the marketing system and the metering automation system, the format normalized state data is associated and integrated based on a preset user ID and transformer number to obtain standard unified state data;

[0037] An information summarizing module is configured to acquire a data theme of the standard unified state data, and to store the standard unified state data in a preset middle platform database based on the data theme to obtain structured theme data;

[0038] Obtaining the keywords in the structured subject data, a real-time topology tree and an inventory topology tree, and checking whether the nodes of the real-time topology tree and the inventory topology tree are consistent with the keywords as a contrast core, to obtain a list of inconsistent information;

[0039] A line loss evaluation module is configured to send the list of inconsistent information to a marketing system, perform topology updating according to the list type of the list of inconsistent information, obtain an updated marketing system, extract new energy operation library data in the structured subject data, analyze the association between new energy processing and a power distribution network based on the new energy operation library data, obtain an identified application scenario, switch a line loss calculation model based on the identified application scenario, obtain an adjusted line loss calculation model, and perform line loss verification and evaluation by using the adjusted line loss calculation model and the updated marketing system.

[0040] To solve the above problems, the present application further provides an electronic device, which comprises:

[0041] at least one processor; and

[0042] a memory connected to the at least one processor in communication; wherein

[0043] The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the line loss verification and evaluation method based on marketing and distribution data as described above.

[0044] To solve the above problems, the present application further provides a computer readable storage medium, comprising a storage data area and a storage program area, the storage data area stores created data, and the storage program area stores a computer program; wherein the computer program is executed by a processor to implement the line loss verification and evaluation method based on marketing and distribution data as described above.

[0045] The embodiment of the application obtains real-time data from a marketing and metering system according to a line loss target and a data threshold, and obtains preliminary cleaning data through synchronization, deduplication and verification; after unifying the format, the preliminary cleaning data is associated and integrated into standard data by using a user ID and a transformer number, and is stored in a structured data according to a theme. Inconsistent lists of real-time and registered topology trees are checked, and the marketing system is updated; new energy data is analyzed to identify a scene, a line loss model is switched, and line loss verification is completed in combination with the updated system. Therefore, the line loss verification and evaluation method and device based on marketing and distribution data, the electronic equipment and the computer readable storage medium provided by the application can realize automatic synchronization of multi-system data, real-time checking of topology relations, replacement of manual operation, avoidance of data lag and omissions, ensuring consistency of the marketing system topology and the field, and improving the accuracy of the line loss calculation basic data. Meanwhile, for the complex power flow problem caused by the access of new energy, the line loss model is dynamically switched through scene identification, the complex working conditions are adapted, the fine management demand is met, and the intelligent level of line loss management and control is improved. BRIEF DESCRIPTION OF DRAWINGS

[0046] Figure 1 A flowchart of a line loss verification and evaluation method based on marketing and distribution data provided by an embodiment of the application is shown.

[0047] Figure 2 A module diagram of a line loss verification and evaluation device based on marketing and distribution data provided by an embodiment of the application is shown.

[0048] Figure 3 An internal structure diagram of an electronic equipment for implementing the line loss verification and evaluation method based on marketing and distribution data provided by an embodiment of the application is shown.

[0049] The implementation, functional features and advantages of the application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0050] It should be understood that the specific embodiments described herein are only used to explain the application, and are not used to limit the application.

[0051] The embodiment of the application provides a line loss checking and evaluation method based on marketing and distribution data. The execution subject of the line loss checking and evaluation method based on marketing and distribution data includes but is not limited to at least one of electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the application. The server can be an independent server, or a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks (CDN), and basic cloud computing services such as big data and artificial intelligence platforms. In other words, the line loss checking and evaluation method based on marketing and distribution data can be executed by software or hardware installed in a remote device or a server device. The software can be a blockchain platform. The server includes but is not limited to a single server, a server cluster, a cloud server, or a cloud server cluster.

[0052] Referring to Figure 1 FIG. 1 is a flowchart of a line loss checking and evaluation method based on marketing and distribution data provided by an embodiment of the application. In this embodiment, the line loss checking and evaluation method based on marketing and distribution data includes the following steps S1-S8:

[0053] S1, based on a preset line loss control target and a data quality threshold, acquiring real-time running state data between a data source system cluster, wherein the data source system cluster includes a marketing system and a metering automation system.

[0054] It can be understood that by presetting the line loss control target and the data quality threshold, the system can automatically extract the running state data from the marketing system and the metering automation system in real time, complete multi-source synchronization, deduplication, format checking and unified normalization, and associate and integrate with the user ID and the transformer number as the key fields, and finally generate accurate, complete and consistent format standard unified state data, thereby laying a reliable data foundation for subsequent topology checking, new energy modeling and line loss evaluation.

[0055] The data source system cluster refers to a group of core business systems that provide original running data for line loss calculation and topology checking. In this scheme, it specifically refers to two main members, the marketing system and the metering automation system, which form a cluster through interface services and jointly deliver data to the data center in real time.

[0056] The marketing system refers to a power enterprise's power consumption marketing comprehensive management information system, saves user archives, registered household-transformer topology relations, power and electricity charges, service work orders and other static and quasi-static data, and is an authoritative data source of "customer side" in line loss statistics; the metering automation system refers to a system responsible for real-time collection, transmission and storage of on-site metering devices (smart meters, measurement terminals), and provides voltage, current, power, power and real-time household-transformer topology and other "second / minute" operation data, and is a real-time data source of "device side" in line loss calculation.

[0057] The line loss control target refers to a quantitative control index set for distribution network line loss management, such as "10kV transformer area monthly line loss rate ≤8%, daily line loss rate fluctuation ≤±1%", and is used to guide data collection range, calculation frequency and abnormality discrimination standards.

[0058] The data quality threshold refers to a quality threshold set for original data to ensure the reliability of line loss calculation, and usually includes integrity: missing field proportion ≤5%; accuracy: voltage / current error ≤±2%; timeliness: data delay ≤15min; and exceeding any threshold triggers a cleaning or supplementary collection process.

[0059] In the embodiment of the application, based on the preset line loss control target and data quality threshold, real-time operation state data between data source system clusters is acquired, including:

[0060] A standardized data interface of the data source system cluster is acquired, and data acquisition rules for each data source system in the data source system cluster are configured based on the line loss control target and the data quality threshold, wherein the data acquisition rules include that the metering automation system acquires real-time measurement data at 15 minutes / once, new energy data acquisition frequency is set to 5 minutes / once, the smart measurement terminal acquires user-transformer association information at 15 minutes / once, and data is encrypted and uploaded to the metering automation system through a power wireless private network;

[0061] Based on the standardized data interface, the state data is acquired by using the data acquisition rules to obtain initial state data, and the initial state data is subjected to format checking, integrity checking and timeliness checking to obtain real-time operation state data, wherein the real-time operation state data includes dynamic topology, electrical measurement and static basic data.

[0062] S2, multi-system synchronization is performed on the real-time operation state data between the data source system clusters to obtain synchronized state data, and the synchronized state data is subjected to de-duplication and format checking to obtain preliminary cleaned state data.

[0063] It can be understood that by "second-level alignment" of real-time data from multiple systems such as marketing, metering automation, and new energy management, de-duplication and unified format, eliminating duplication, misplacement and format confusion from the source, ensuring that each piece of data used for subsequent line loss calculation is unique, standardized and immediately usable "clean" data.

[0064] Among them, the synchronization state data refers to the real-time running state data (such as device online state, data transmission rate, node load, data synchronization progress, etc.) of each subsystem in the data source system cluster after being processed by a multi-system synchronization mechanism (such as a distributed consistency protocol, real-time data mirroring, etc.), forming a data set reflecting the running state of each system and achieving cross-system information alignment.

[0065] Among them, the preliminary cleaning state data refers to the state data with basic validity, no duplication and standardized format obtained after "de-duplication" (eliminating duplicate records to avoid data redundancy) and "format verification" (checking whether the data conforms to the preset format specification, such as field type, structure, value range, etc., excluding format error data) of the synchronization state data (real-time running state data) obtained by synchronizing the data source system cluster. It is the initial achievement of data cleaning, providing a basis for subsequent deeper cleaning (such as handling missing values, outliers, etc.) or direct use.

[0066] Further, the multi-system synchronization of the real-time running state data between the data source system cluster, obtaining the synchronization state data, and de-duplicating and formatting the synchronization state data to obtain the preliminary cleaning state data, include:

[0067] Unify the time base of each data source system in the data source cluster through a preset clock synchronization protocol, and eliminate data with a collection time difference exceeding a preset time threshold. Sort the real-time running state data by collection timestamp to obtain sorted running data;

[0068] Based on the preset user ID, transformer number, and collection timestamp, a hash index is constructed, and the hash index is used to identify and eliminate duplicate records in the sorted running data. The latest version is retained for duplicate data with version differences in the sorted running data to obtain the synchronization state data;

[0069] According to the preset JSON schema, the data format is verified, the fields in the synchronization state data that do not conform to the specification are converted or marked as abnormal, and the data records lacking key information are supplemented or eliminated, and a log file containing abnormal verification results is generated;

[0070] The data in the log file is reorganized according to the preset standard data structure, supplemented with data source identification and data quality score, and the preliminary cleaning state data is obtained.

[0071] Among them, the clock synchronization protocol is a standardized rule for unifying the time reference of each system in the data source cluster (such as NTP, PTP), which ensures the consistency of the timestamps of the data collected by each system by eliminating the time difference caused by hardware clock deviation, network delay, etc., and provides a unified time reference for subsequent data sorting and deduplication.

[0072] Among them, the time threshold is a critical value for judging the validity of data collection time, which is usually set according to the real-time business requirements (such as 1-30 seconds), and when the difference between the data collection time and the unified reference time exceeds the threshold, it is determined as time abnormal data and is excluded, avoiding the impact on data accuracy due to time confusion.

[0073] Among them, JSON schema is a specification for describing and validating JSON data structure (or called "metadata"), which defines the fields allowed in JSON data, the data types of fields (such as string, number, boolean, etc.), the constraints of fields (such as whether it is required, value range, format requirements, etc.), and the relationship between fields, which is equivalent to the "format specification" or "check rules" of JSON data.

[0074] Among them, the log file is a file that records the details of abnormal data in the JSON schema validation process, which usually includes the unique identifier of the abnormal data, the type of abnormality (such as missing key fields, format errors), the original data content, and the validation time, etc., providing abnormal clues for data operation personnel, facilitating traceability and repair, and retaining the basis for data quality validation.

[0075] S3, based on the preset format adjustment rule, the format of the preliminary cleaning state data is unified to obtain the format normalized state data, and according to the marketing system and the metering automation system, the format normalized state data is associated and integrated by using the preset user ID and transformer number to obtain the standard unified state data.

[0076] It can be understood that by unifying the data format across systems to eliminate the format differences between the marketing system and the metering automation system, and then associating and integrating the data of the two systems with user ID and transformer number as the link, not only the data interconnection obstacles caused by format confusion are solved, but also the data silos between systems are broken, forming a complete data chain with standardized format and logical association, providing a unified and coherent data basis for subsequent topology checking, new energy data analysis, and line loss verification, etc., directly improving the accuracy and efficiency of subsequent data processing and business decision-making.

[0077] The format adjustment rule refers to a standardized specification set for unifying the preliminary cleaning state data format, mainly including field name unification (such as unifying the "user number" of the marketing system and the "user ID" of the metering automation system as "user ID"), data type conversion (such as converting string type time into standard timestamp format), unit standardization (such as unifying the electric quantity unit as "kilowatt hour"), and the like, aiming to eliminate the format differences caused by different development standards of the two systems, and ensure the consistency of data in field naming, type, format and the like.

[0078] The standard unified state data refers to a complete data set associated and integrated through user ID and transformer number (cross-system common identifier) after format normalization, which contains not only user basic information, electricity contract data and the like of the marketing system, but also real-time metering, device running state data and the like of the metering automation system, forms an integrated data with user / device as the core, unified format and logical association, solves the problem of "format inconsistency and association fracture" of cross-system data, and provides a standardized data basis for subsequent storage, analysis and business application.

[0079] Further, the format of the preliminary cleaning state data is unified based on the preset format adjustment rule to obtain format normalized state data, and the format normalized state data is associated and integrated based on the user ID and the transformer number to obtain standard unified state data, including:

[0080] Each system field in the preliminary cleaning state data is uniformly converted based on the format adjustment rule to obtain format normalized state data;

[0081] The format normalized state data is adjusted in topology based on the user ID and the transformer number to obtain topology structure data, and the integrated data of the topology structure data is packaged in a unified JSON format to obtain standard unified state data, wherein the format of the topology structure data is district-transformer-user-new energy.

[0082] The preset rule is, for example, a CIM model standard, the different format data is, for example, an Excel table of the marketing system and JSON data of the metering automation, and the unified structure is, for example, a topology tree JSON format.

[0083] The real-time topology data refers to dynamic topology structure data reflecting the current actual connection relationship of power users, transformers and the like collected in real time from data sources such as the metering automation system, containing real-time physical connection, running association and the like node information between devices, dynamically updated with the actual running state of the system, and embodying the current real topology running condition.

[0084] The in-register topological data refers to theoretical topological structure data formed based on user archives and equipment account records in a marketing system, records registered association of users and transformers and other equipment, and connection relationship of archive registration, belongs to static basic archive information, and reflects standard topological state registered and recorded by the system.

[0085] S4, acquire data topics of the standard unified state data, and store the standard unified state data to a preset middle platform database based on the data topics, to obtain structured topic data.

[0086] The middle platform database is a core storage system in a data middle platform architecture, and is used for centralized storage of integrated data of cross-business systems (such as integrated data of a marketing system and a metering automation system) after standardization and integration. It is different from independent databases of various business systems, and organizes data according to data topics (such as user domain, equipment domain, and operation domain) or business dimensions, supports unified management, shared calling, and rapid service of data, provides stable and consistent data support for various upper-layer business applications (such as line loss management and control, topology updating, and new energy analysis), and is a key storage carrier for realizing a data “big middle platform and small front platform” architecture.

[0087] It can be understood that by storing the standard unified state data to the middle platform database according to data topics, the data forms structured topic data with clear classification and logical association, realizes centralized management and thematic ordered storage of cross-system data, avoids disordered accumulation, improves reusability of the data, facilitates shared calling of multiple upper-layer applications, and provides standardized and unified data input for subsequent topology checking, new energy analysis, line loss calculation, and other business links, thereby laying a foundation for accurate and efficient data analysis and business decision-making.

[0088] S5, acquire keywords in the structured topic data, real-time topology tree and in-register topology tree, and compare the keywords to check whether nodes of the real-time topology tree and the in-register topology tree are consistent, to obtain an inconsistent information list.

[0089] It can be understood that by checking the consistency of the nodes of the real-time topology tree (reflecting the actual running topology connection) and the registered topology tree (reflecting the registered theoretical topology connection) based on the keyword, the deviation of the two in device association and connection relationship (such as the node that the actual connection does not match the archive registration) can be accurately identified, and the inconsistent information list formed by the summary can make the dispersed topology difference explicit and listed. This not only provides a clear rectification basis for subsequent topology data correction (such as updating the registered topology to match the actual operation), but also lays the foundation for eliminating the line loss calculation deviation and marketing archive errors caused by topology inconsistency, while promoting the dynamic alignment of real-time running data and registered archive data, improving the accuracy and consistency of power system topology data, and supporting more accurate business decisions (such as line loss control and equipment maintenance).

[0090] Among them, the keyword refers to the core field used to uniquely identify or associate the nodes of the real-time topology tree and the registered topology tree, which is the "baseline identification" for consistency checking. It usually includes user ID, transformer number, meter asset number, line identification, and other unique identifiers common across topology trees, ensuring accurate positioning of the corresponding relationship of the same node (such as the same user or the same transformer) in the two topology trees during checking.

[0091] Among them, the real-time topology tree refers to a tree-shaped topology structure model constructed based on real-time topology data, with nodes (such as users, transformers, branch lines, and distribution areas) as basic units, and edges (connection relationships) reflecting the actual running connection hierarchy of each node (such as the real-time affiliation of "distribution area-transformer-user"), dynamically updated with real-time topology data, and intuitively presenting the current actual running topology hierarchy and connection logic of the power system.

[0092] Among them, the registered topology tree refers to a tree-shaped topology structure model constructed based on registered topology data, also with nodes (users, transformers, and lines) as units, and edges reflecting the theoretical connection hierarchy of each node registered in the archive (such as the registered affiliation of "distribution area-transformer-user"), generated based on static archive information, not changing with real-time running state, and embodying the standard topology hierarchy and connection logic registered by the system.

[0093] Among them, the inconsistent information list refers to the specific information found when checking the real-time topology tree and the registered topology tree based on the keyword, which does not match the node attributes or connection relationships. For example: the transformer number associated with a user (keyword: user ID) in the real-time topology tree does not match the transformer number registered in the registered topology tree; or a transformer (keyword: transformer number) exists in the real-time topology tree but has no registration record in the registered topology tree. These information directly reflects the deviation between the actual running topology and the registered topology, and is the key basis for subsequent topology correction and data calibration.

[0094] Further, after the inconsistent node information is summarized to obtain the inconsistent information list, the method further comprises:

[0095] returning the updated on-roll topology data of the marketing system to the preset middle platform;

[0096] classifying the inconsistent information list according to problem types to generate a processing work order containing problem descriptions, influence ranges and priorities;

[0097] based on the processing work order, triggering a correction process by using the marketing system, obtaining simple problems and complex problems in the processing work order, and processing them respectively to obtain the processing work order.

[0098] The marketing system returns the updated on-roll topology data to the middle platform; the inconsistent information list is classified according to problem types to generate a processing work order containing problem descriptions, influence ranges and priorities; the marketing system triggers a correction process based on the processing work order, simple problems are automatically processed, complex problems are assigned to be checked on site, and all corrections are recorded in a version; the marketing system encapsulates the updated topology data according to the interface specifications of the middle platform to obtain standardized topology update data packets, wherein the standardized topology update data packets contain changed nodes, time stamps and MD5 check codes; the marketing system returns data to the middle platform through a message queue or a timing task, the middle platform updates the on-roll topology database and the associated theme database after verifying the verification code; the middle platform feeds back the update result to the marketing system, and detailed logs are attached when the update fails, and the marketing system is accordingly modified again until a closed loop is formed.

[0099] It can be understood that by standardizing and encapsulating the updated topology data of the marketing system, generating work orders according to categories for hierarchical processing (automatic + manual) and keeping version records, and combining with the check code to ensure transmission safety, the middle platform verification and feedback closed loop mechanism, the marketing system and the middle platform topology data are accurately consistent, the processing efficiency of topology deviation problems is improved, the whole process is kept traceable, and finally a complete closed loop from deviation discovery to correction synchronization is formed, which provides accurate and reliable topology data support for subsequent business.

[0100] S6, send the inconsistent information list to the marketing system, update the topology according to the list type of the inconsistent information list, obtain an updated marketing system, extract new energy operation library data in the structured theme data, analyze the association between new energy processing and the power distribution network based on the new energy operation library data, obtain an identified application scenario, switch a line loss calculation model based on the identified application scenario, obtain an adjusted line loss calculation model, and perform line loss verification and evaluation by using the adjusted line loss calculation model and the updated marketing system.

[0101] It can be understood that by pushing the marketing system topology data update to ensure the accuracy of the basic data, combined with the new energy operation data to identify the application scene and adapt the line loss calculation model, finally using the accurate topology data and the adapted model to carry out line loss verification and evaluation, not only eliminates the interference of topology deviation on the evaluation, but also makes the line loss calculation dynamically match the correlation characteristics of new energy and distribution network, thereby significantly improving the accuracy and reliability of line loss verification and evaluation, providing accurate basis for line loss control, new energy grid connection optimization and other business decisions.

[0102] Among them, the new energy operation library data is a structured collection of basic attributes (type, capacity, access point, etc.), real-time / historical operation parameters (power generation, power, grid-connected state, etc.), operation exception records, and interaction data (access node, load impact, etc.) of distributed new energy equipment such as photovoltaic, wind power, energy storage, and charging piles, used to analyze the correlation between new energy and distribution network, support line loss calculation model to adapt and switch according to application scenarios, and ensure that line loss verification and evaluation are consistent with the actual operation state of the distribution network after new energy access.

[0103] Further, the extraction of new energy operation library data in structured topic data, based on the new energy operation library data, analyzes the correlation between new energy and distribution network, and obtains the identified application scenario, including:

[0104] Collect new energy operation library data in structured topic data, and upload the new energy operation data after encryption, as well as format, integrity, and timeliness verification, to obtain structured new energy operation data;

[0105] Analyze the fusion topology and load data in the structured new energy operation data, output fluctuation and voltage deviation, access capacity and carrying capacity, and mine the quantitative correlation between new energy and the preset distribution network, to obtain the correlation identification result;

[0106] Based on the correlation identification result, identify the typical application scenarios of distribution network voltage regulation, consumption optimization, carrying capacity evaluation, and fault warning, to obtain the identified application scenario.

[0107] Further, the line loss verification and evaluation using the adjusted line loss calculation model and the updated marketing system, including:

[0108] Based on the adjusted line loss calculation model and the updated marketing system, output the line loss rate of each sub-district, high-loss anomaly list, and optimization suggestions, and perform line loss verification and evaluation.

[0109] Among them, the high-loss anomaly list includes reason analysis, such as photovoltaic reverse sending leading to virtual high line loss; and optimization suggestions, such as limiting the photovoltaic access capacity of the sub-district to 1MW.

[0110] The embodiment of the application obtains real-time data from a marketing and metering system according to a line loss target and a data threshold, and obtains preliminary cleaning data through synchronization, deduplication and verification; after unifying the format, the preliminary cleaning data is associated and integrated into standard data using a user ID and a transformer number, and is stored in a structured data according to a theme. Inconsistent lists of real-time and registered topology trees are checked, and the marketing system is updated; new energy data is analyzed to identify scenes, and the line loss model is switched, and the line loss verification is completed in combination with the updated system. Therefore, the line loss verification and evaluation method and device based on marketing and distribution data, electronic equipment and computer readable storage medium provided by the application can automatically synchronize multiple system data, check the topology relationship in real time, replace manual operation, avoid data lag and omissions, ensure that the marketing system topology is consistent with the field, and improve the accuracy of the line loss calculation basis data; at the same time, for the complex problem of power flow caused by the access of new energy, the line loss model is dynamically switched through scene recognition, the complex working conditions are adapted, the fine management demand is met, and the intelligent level of line loss management and control is improved.

[0111] As shown in Figure 2 , it is a module schematic diagram of the line loss verification and evaluation device based on marketing and distribution data.

[0112] The line loss verification and evaluation device based on marketing and distribution data 100 can be installed in an electronic equipment. According to the functions to be realized, the line loss verification and evaluation device based on marketing and distribution data can include a data acquisition module 101, a data processing module 102, an information summary module 103 and a line loss evaluation module 104. The modules of the application can also be called units, which refer to a series of computer program segments that can be executed by an electronic equipment processor and can complete fixed functions, and are stored in the memory of the electronic equipment.

[0113] In the embodiment, the functions of each module / unit are as follows:

[0114] The data acquisition module 101 is configured to acquire real-time running state data between a data source system cluster based on a preset line loss management and control target and a data quality threshold, wherein the data source system cluster includes a marketing system and a metering automation system;

[0115] The data processing module 102 is configured to perform multi-system synchronization on the real-time running state data between the data source system cluster to obtain synchronized state data, and perform deduplication and format verification on the synchronized state data to obtain preliminary cleaning state data;

[0116] The format of the preliminary cleaning state data is unified based on a preset format adjustment rule to obtain format normalized state data, and the format normalized state data is associated and integrated using a preset user ID and transformer number according to the marketing system and the metering automation system to obtain standard unified state data;

[0117] The information aggregation module 103 is configured to obtain a data theme of the standard unified state data, and store the standard unified state data into a preset middle platform database based on the data theme, to obtain structured theme data.

[0118] The key word, the real-time topology tree and the registered topology tree in the structured theme data are obtained, and it is checked whether the nodes of the real-time topology tree and the registered topology tree are consistent with the key word as a comparison core, to obtain an inconsistent information list.

[0119] The line loss evaluation module 104 is configured to send the inconsistent information list to a marketing system, to perform topology updating according to the list type of the inconsistent information list, to obtain an updated marketing system, to extract new energy operation library data in the structured theme data, to analyze the correlation between new energy processing and a power distribution network based on the new energy operation library data, to obtain an identified application scenario, to switch a line loss calculation model based on the identified application scenario, to obtain an adjusted line loss calculation model, and to perform line loss verification and evaluation by using the adjusted line loss calculation model and the updated marketing system.

[0120] In detail, each module in the line loss verification and evaluation device 100 based on marketing and distribution data in the embodiment of the present application adopts the same technical means as the line loss verification and evaluation method based on marketing and distribution data described above when in use, and can produce the same technical effects, which will not be described here. Figure 1 The line loss verification and evaluation method based on marketing and distribution data described above.

[0121] As shown in Figure 3 FIG. 1, it is a structural schematic diagram of an electronic device for implementing the line loss verification and evaluation method based on marketing and distribution data.

[0122] The electronic device can include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and can further include a computer program stored in the memory 11 and executable on the processor 10, such as a line loss verification and evaluation program based on marketing and distribution data.

[0123] The processor 10 may, in some embodiments, be composed of integrated circuits, for example, a single packaged integrated circuit, or a plurality of packaged integrated circuits of the same or different functions, including one or more combinations of central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connects various components of the electronic device through various interfaces and lines, executes programs or modules stored in the memory 11 (for example, executes a line loss verification and evaluation program based on distribution data), and calls data stored in the memory 11 to perform various functions and process data of the electronic device.

[0124] The memory 11 includes at least one type of readable storage medium, including flash memories, mobile hard disks, multimedia cards, card-type memories (for example, SD or DX memories, etc.), magnetic memories, magnetic disks, optical disks, etc. The memory 11 may, in some embodiments, be an internal storage unit of the electronic device, for example, a mobile hard disk of the electronic device. The memory 11 may, in other embodiments, also be an external storage device of the electronic device, for example, a plug-in mobile hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 11 may include both an internal storage unit and an external storage device of the electronic device. The memory 11 can be used not only to store application software and various data installed in the electronic device, for example, codes of a line loss verification and evaluation program based on distribution data, but also to temporarily store data that has been or will be output.

[0125] The communication bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to realize the connection and communication between the memory 11 and at least one processor 10, etc.

[0126] The communication interface 13 is used for communication between the electronic device and other devices, including a network interface and a user interface. Optionally, the network interface can include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is usually used to establish a communication connection between the electronic device and other electronic devices. The user interface can be a display (Display), an input unit (such as a keyboard (Keyboard)), and optionally, the user interface can also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display can be an LED display, a liquid crystal display, a touch liquid crystal display, and an OLED (Organic Light-Emitting Diode) touch, etc. Among them, the display can also be appropriately called a display screen or a display unit, which is used to display information processed in the electronic device and to display a visual user interface.

[0127] Figure 3 Only the electronic device with components is shown, and those skilled in the art can understand that, Figure 3 The structure shown does not constitute a limitation on the electronic device, and can include fewer or more components than shown, or combine certain components, or different component arrangements.

[0128] For example, although not shown, the electronic device can also include a power supply (such as a battery) for powering each component. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, so that functions such as charge management, discharge management, and power consumption management can be realized through the power management device. The power supply can also include one or more direct current or alternating current power sources, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and any other components. The electronic device can also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which are not described here.

[0129] It should be understood that the embodiments are only for illustration and are not limited in the scope of the patent application by this structure.

[0130] The line loss verification and evaluation program based on marketing data stored in the memory 11 in the electronic device is a combination of multiple computer programs, which, when running in the processor 10, can realize:

[0131] Based on the preset line loss control target and data quality threshold, real-time running state data between data source system clusters is obtained, wherein the data source system clusters include a marketing system and a metering automation system;

[0132] Multi-system synchronization is performed on real-time running state data between the data source system clusters to obtain synchronized state data, and the synchronized state data is subjected to deduplication and format checking to obtain preliminary cleaned state data;

[0133] The format of the preliminary cleaned state data is unified based on preset format adjustment rules to obtain format normalized state data, and the format normalized state data is subjected to key field association and integration based on the marketing system and the metering automation system by using a preset user ID and a transformer number to obtain standard unified state data;

[0134] The data theme of the standard unified state data is obtained, and the standard unified state data is stored into a preset middle platform database based on the data theme to obtain structured theme data;

[0135] The key word in the structured theme data, the real-time topology tree and the registered topology tree are obtained, and it is checked whether the nodes of the real-time topology tree and the registered topology tree are consistent by taking the key word as a comparison core to obtain an inconsistent information list;

[0136] The inconsistent information list is sent to the marketing system, the topology is updated according to the list type of the inconsistent information list to obtain an updated marketing system, the new energy running library data in the structured theme data is extracted, the association relationship between new energy processing and a power distribution network is analyzed based on the new energy running library data, an identification application scenario is obtained, the line loss calculation model is switched based on the identification application scenario to obtain an adjusted line loss calculation model, and the line loss calculation model and the updated marketing system are used for line loss checking and evaluation.

[0137] Specifically, the specific implementation method of the processor 10 to the above computer program can refer to Figure 1 The description of related steps in the corresponding embodiments will not be repeated here.

[0138] Further, the modules / units integrated in the electronic device, if realized in the form of software function units and sold or used as independent products, can be stored in a nonvolatile computer readable storage medium. The computer readable storage medium can be volatile or nonvolatile. For example, the computer readable medium can include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM).

[0139] The application further provides a computer readable storage medium, which stores a computer program, and the computer program can realize the following when executed by a processor of an electronic device:

[0140] Based on the preset line loss control target and data quality threshold, real-time running state data between data source system clusters is acquired, wherein the data source system clusters include a marketing system and a metering automation system;

[0141] The real-time running state data between the data source system clusters is synchronized, and synchronized state data is obtained, and the synchronized state data is de-duplicated and format-verified, and preliminary cleaning state data is obtained;

[0142] Based on a preset format adjustment rule, the format of the preliminary cleaning state data is unified, and format-normalized state data is obtained, and according to the marketing system and the metering automation system, the format-normalized state data is associated and integrated based on a preset user ID and a transformer number, and standard unified state data is obtained;

[0143] The data theme of the standard unified state data is acquired, and the standard unified state data is stored into a preset middle platform database based on the data theme, and structured theme data is obtained;

[0144] The key word, real-time topology tree and on-the-record topology tree in the structured theme data are acquired, and it is checked whether the nodes of the real-time topology tree and the on-the-record topology tree are consistent with the key word as a comparison core, and an inconsistent information list is obtained;

[0145] The inconsistent information list is sent to the marketing system, the topology is updated according to the list type of the inconsistent information list, and an updated marketing system is obtained, the new energy running library data in the structured theme data is extracted, the association relationship between new energy processing and a power distribution network is analyzed based on the new energy running library data, an identification application scenario is acquired, the line loss calculation model is switched based on the identification application scenario, an adjusted line loss calculation model is obtained, and the adjusted line loss calculation model and the updated marketing system are used for line loss checking and evaluation.

[0146] In several embodiments provided in the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other manners. For example, the above-described apparatus embodiments are merely schematic. For example, the division of the modules is merely a logical function division. There can be another division manner in actual implementation.

[0147] The modules illustrated as separated components can or can not be physically separated, and the components illustrated as modules can or can not be physical units. That is, they can be located in one place, or distributed on a plurality of network units. According to actual needs, some or all of the modules can be selected to achieve the purpose of the embodiments.

[0148] In addition, each functional module in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware, or in the form of hardware plus software function module.

[0149] It is obvious for those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and the present application can be realized in other specific forms without departing from the spirit or essential characteristics of the present application.

[0150] Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting, the scope of the present application is defined by the appended claims rather than the above description, and therefore all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present application. Any additional reference signs in the claims should not be considered as limiting the claims involved.

[0151] The blockchain referred to in the present application is a new application mode of distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm and other computer technologies. Blockchain, in essence, is a decentralized database, which is a series of data blocks associated using cryptography. Each data block contains information about a batch of network transactions, used to verify the validity of the information (anti-fake) and generate the next block. The blockchain can include a blockchain underlying platform, a platform product service layer, and an application service layer.

[0152] The embodiments of the present application can acquire and process related data based on artificial intelligence technology. Among them, artificial intelligence (Artificial Intelligence, AI) is to use digital computers or digital computer controlled machines to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0153] In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. The plurality of units or devices stated in the system claims can also be realized by one unit or device through software or hardware. The second word is used to indicate the name, and does not mean any specific order.

[0154] Finally, it should be pointed out that the above embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the technical solutions of the present application.

Claims

1. A line loss verification and evaluation method based on network planning data, characterized in that, The method comprises: Based on the preset line loss control target and data quality threshold, the real-time running state data between the data source system cluster is obtained, wherein the data source system cluster comprises a marketing system and a metering automation system; The real-time running state data between the data source system cluster is synchronized, the synchronized state data is obtained, and the synchronized state data is de-duplicated and format-verified to obtain preliminary cleaning state data; Based on the preset format adjustment rule, the format of the preliminary cleaning state data is unified to obtain format normalized state data, and according to the marketing system and the metering automation system, the format normalized state data is associated and integrated by using a preset user ID and a transformer number to obtain standard unified state data; The data theme of the standard unified state data is obtained, and the standard unified state data is stored in a preset middle platform database based on the data theme to obtain structured theme data; The key word, real-time topology tree and on-the-record topology tree in the structured theme data are obtained, and it is checked whether the nodes of the real-time topology tree and the on-the-record topology tree are consistent with the key word as a comparison core to obtain an inconsistent information list; The inconsistent information list is sent to the marketing system, the topology is updated according to the list type of the inconsistent information list to obtain an updated marketing system, the new energy running library data in the structured theme data is extracted, the association relationship between new energy processing and a power distribution network is analyzed based on the new energy running library data, an identification application scenario is obtained, the line loss calculation model is switched based on the identification application scenario to obtain an adjusted line loss calculation model, and the line loss calculation model and the updated marketing system are used for line loss checking and evaluation.

2. The method for line loss verification and evaluation based on the operation and distribution data according to claim 1, wherein, The method comprises: The standardized data interface of the data source system cluster is obtained, and data acquisition rules are configured for each data source system in the data source system cluster based on the line loss control target and data quality threshold, wherein the data acquisition rules comprise that the metering automation system measures data at 15 minutes / second, the new energy data acquisition frequency is set to 5 minutes / second, the intelligent measurement terminal collects user-transformer association information at 15 minutes / second, and the data is encrypted and uploaded to the metering automation system through the power wireless private network; Based on the standardized data interface, the state data is obtained by using the data acquisition rules to obtain initial state data, and the initial state data is format-verified, integrity-verified and timeliness-verified to obtain real-time running state data, wherein the real-time running state data comprises dynamic topology, electrical measurement and static basic data.

3. The method for line loss verification and evaluation based on the operation and distribution data according to claim 1, wherein, The method comprises: The time reference of each data source system in the data source cluster is unified through a preset clock synchronization protocol, data with a collection time difference exceeding a preset time threshold is removed, real-time running state data is sorted according to a collection time stamp, and sorted running data is obtained; A hash index is constructed based on a preset user ID, transformer number and collection time stamp, repeated records in the sorted running data are identified and removed through the hash index, the latest version is retained for repeated data with version differences in the sorted running data, and synchronized state data is obtained; The data format is checked according to a preset JSON schema, fields in the synchronized state data that do not conform to the specification are converted or marked as abnormal, and data records lacking key information are supplemented or removed, and a log file containing abnormal checking results is generated; The data in the log file is reorganized according to a preset standard data structure, data source identification and data quality scores are supplemented, and preliminary cleaning state data is obtained.

4. The method for line loss verification and evaluation based on the operation and maintenance data according to claim 1, wherein, The format of the preliminary cleaning state data is unified based on a preset format adjustment rule, format normalized state data is obtained, and the format normalized state data is associated and integrated based on the marketing system and the metering automation system using a preset user ID and transformer number, and standard unified state data is obtained, including: Each system field in the preliminary cleaning state data is uniformly converted based on the format adjustment rule, and format normalized state data is obtained; The format normalized state data is adjusted to a topology structure based on the user ID and the transformer number, topology structure data is obtained, and the integrated data of the topology structure data is packaged in a unified JSON format, and standard unified state data is obtained, wherein the format of the topology structure data is district-transformer-user-new energy.

5. The method for line loss verification and evaluation based on the operation and maintenance data according to claim 1, wherein, After all inconsistent node information is summarized to obtain an inconsistent information list, the method further includes: The updated registered topology data of the marketing system is returned to a preset platform; The inconsistent information list is classified according to problem types, and a processing work order containing problem descriptions, impact ranges and priorities is generated; Based on the processing work order, the marketing system triggers a correction process to obtain simple problems and complex problems in the processing work order, and processes them respectively to obtain a processing work order.

6. The method for line loss verification and evaluation based on the operation and maintenance data according to claim 1, wherein, The new energy running library data in the structured topic data is extracted, the association between new energy processing and the power distribution network is analyzed based on the new energy running library data, an application scenario is obtained, including: The new energy running library data in the structured topic data is collected, and the new energy running data is encrypted and uploaded, and format, integrity and timeliness checks are performed to obtain structured new energy running data; The fusion topology and load data in the structured new energy running data are analyzed, and output fluctuation and voltage deviation, access capacity and carrying capacity are obtained, the quantitative association between new energy processing and the preset power distribution network is mined, and an association recognition result is obtained; The typical application scenarios of distribution voltage regulation, consumption optimization, load carrying assessment, and fault early warning are identified based on the association recognition result, and an application scenario is obtained.

7. The method for line loss verification and evaluation based on network planning data according to any one of claims 1 to 6, characterized in that, The line loss verification and evaluation is performed by using the adjusted line loss calculation model and the updated marketing system, including: The line loss verification and evaluation is performed by using the adjusted line loss calculation model and the updated marketing system, including:

8. A line loss verification and evaluation device based on operation and distribution data, characterized by, The device comprises: The data acquisition module is configured to acquire real-time running state data between data source system clusters based on preset line loss management and control targets and data quality thresholds, wherein the data source system clusters include a marketing system and a metering automation system; The data processing module is configured to perform multi-system synchronization on the real-time running state data between the data source system clusters to obtain synchronized state data, and perform deduplication and format verification on the synchronized state data to obtain preliminary cleaned state data; The format of the preliminary cleaned state data is unified based on a preset format adjustment rule to obtain format normalized state data, and the format normalized state data is integrated based on a preset user ID and transformer number to obtain standard unified state data according to the marketing system and the metering automation system; The information aggregation module is configured to acquire data topics of the standard unified state data, and store the standard unified state data into a preset middle platform database based on the data topics to obtain structured topic data; The line loss evaluation module is configured to send the inconsistent information list to the marketing system, perform topology update according to the list type of the inconsistent information list to obtain an updated marketing system, extract new energy running library data from the structured topic data, analyze the association between new energy processing and the power distribution network based on the new energy running library data, acquire an application scenario, switch a line loss calculation model based on the application scenario, obtain an adjusted line loss calculation model, and perform line loss verification and evaluation by using the adjusted line loss calculation model and the updated marketing system. The electronic device comprises:

9. An electronic device, comprising: at least one processor; and a memory connected with the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the line loss verification and evaluation method based on marketing and distribution data according to any one of claims 1 to 7. The computer program is executed by the processor to implement the line loss verification and evaluation method based on marketing and distribution data according to any one of claims 1 to 7.

10. A computer readable storage medium comprising a storage data area and a storage program area, the storage data area storing created data, the storage program area storing a computer program; wherein, ​

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