An Internet of Vehicles measurement data access method, electronic device, computer readable storage medium, computer program product

Abstract

The application provides a vehicle networking measurement data access method, electronic equipment, a computer readable storage medium and a computer program product, which comprises the following steps: storing real-time vehicle networking measurement data into a data bus; performing real-time analysis and conversion on the vehicle networking measurement data in the data bus, and storing the analyzed and converted vehicle networking measurement data into a standard collection queue according to different types; accessing the vehicle networking measurement data by consuming the vehicle networking measurement data in the standard collection queue; and generating the standard collection queue according to the following steps: associating and mapping the vehicle networking measurement data with vehicle networking static account data to obtain an association mapping result; generating a measurement point and measurement point information for the vehicle networking measurement data according to the association mapping result; and generating the standard collection queue according to the measurement point and the measurement point information. The application solves the problems of real-time transmission of massive vehicle networking interactive data, multi-dimensional vehicle networking data association and management of large-scale load data collection, transmission and storage.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of electric power, and particularly relates to a vehicle networking measurement data access method, an electronic device, a computer readable storage medium, and a computer program product. BACKGROUND

[0002] The large-scale development of electric vehicles and charging facilities increases the access pressure of distribution networks and provides important flexible regulation resources for new power systems. At present, there is no comprehensive and normalized vehicle-to-grid interaction business, and the participation scale is limited. However, with the continuous growth of new energy vehicle penetration rate and the increase of the number of vehicles, promoting vehicle-to-grid integration is increasingly important for the construction of new power systems.

[0003] The enterprise-level measurement center is an important part of the power grid resource business platform. It online unifies and gathers the measurement data of electric and non-electric types in each link of the power grid, and supports high-speed sharing applications of each professional in a real-time forwarding service mode, and continuously deposits collection measurement sharing services. However, the measurement center has not yet gathered the use and collection data of the vehicle networking system, resulting in that the vehicle-to-grid integration still lacks panoramic observation analysis capabilities of relevant business elements of the electric vehicle charging load in the “region-station-line-transformer-house-load” hierarchical classification in the aspect of digital support, cannot efficiently and accurately connect to the power grid, relies on manual maintenance, has low efficiency and high cost, cannot fully support power grid charging load monitoring and characteristic analysis, cannot fully support the development of operation and management risk prediction and adjustable capacity mining, cannot guide the power grid to develop reasonable capacity expansion and network construction, and cannot support the growth of electric vehicles and the development of vehicle-to-grid business.

[0004] Therefore, it is urgent to build a vehicle networking measurement data access system. In the development of the system, the following problems exist:

[0005] (1) It is difficult to realize real-time transmission of massive vehicle networking measurement data: vehicle-to-grid interaction data needs to be transmitted across systems and regions, and the data concurrency is large and the transmission link is long. The existing transmission capacity cannot meet the real-time requirements;

[0006] (2) The correlation accuracy of vehicle networking measurement data and power grid resource account data is low: the vehicle networking measurement data of the enterprise-level measurement center needs to be accurately correlated with the account data of the power grid resource business platform, so as to stimulate the panoramic observation analysis capabilities of relevant business elements of the charging load in the hierarchical classification, and efficiently and accurately connect to the power grid. However, the vehicle networking measurement data and the account data come from different systems, and the data models and update frequencies are different, resulting in great difficulty in cross-domain correlation matching and low accuracy, and it is difficult to support the panoramic perception of charging load resources;

[0007] (3) Large-scale load data storage persistence continuity difficult: the unified basic digital model of charging load has not been established, the global unified resource code is lacking, the quality of multi-source data is uneven, the data is not connected, the storage method is imperfect, and the ability to share and apply diversified charging resources is not available. SUMMARY

[0008] The application aims to solve the problems existing in the development of vehicle networking measurement data access system, and provides a vehicle networking measurement data access method, electronic equipment, computer readable storage medium and computer program product.

[0009] Technical scheme: in the first aspect, a vehicle networking measurement data access method comprises:

[0010] store real-time vehicle networking measurement data in the data bus;

[0011] real-time analysis and conversion of vehicle networking measurement data in the data bus, and storage of the analyzed and converted vehicle networking measurement data in the standard collection queue according to different types;

[0012] by consuming vehicle networking measurement data in the standard collection queue, the access of vehicle networking measurement data is realized;

[0013] wherein, the standard collection queue is generated according to the following steps:

[0014] associate vehicle networking measurement data with vehicle networking static account data to obtain an association mapping result;

[0015] generate measurement points and measurement point information for vehicle networking measurement data according to the association mapping result;

[0016] generate a standard collection queue according to the measurement points and measurement point information.

[0017] Further, the real-time vehicle networking measurement data is stored in the data bus, specifically including:

[0018] store real-time vehicle networking measurement data by using message queue;

[0019] The vehicle networking measurement data in the message queue is parsed and written into the data table of the intermediate library deployed in the management information area; according to the measurement data type, the vehicle networking measurement data in the message queue is one-to-one corresponding to the data table of the intermediate library;

[0020] The vehicle networking measurement data in the data table of the intermediate library is synchronized to the data bus.

[0021] Further, the vehicle networking measurement data includes: charging gun charging state telemetry data, charging gun charging device state change telesign data and charging gun charging order event data; the charging gun charging state telemetry data, the charging gun charging device state change telesign data and the charging gun charging order event data are associated through device interface coding.

[0022] Correspondingly, the data table of the intermediate library includes: the charging gun charging state data table, the charging gun charging device state change data table and the charging gun charging order event data table.

[0023] Further, the real-time vehicle networking measurement data is stored by using the message queue, specifically including:

[0024] Obtaining vehicle networking measurement data;

[0025] Using Nginx load balancing service and peak clipping service, the vehicle networking measurement data is pushed into the RocketMQ message queue for storage.

[0026] Further, the vehicle networking measurement data is associated and mapped with the vehicle networking static account data to obtain an association and mapping result; measurement points and measurement point information are generated for the vehicle networking measurement data according to the association and mapping result, specifically including:

[0027] Scanning the vehicle networking static account data of the power grid resource business platform and the vehicle networking measurement data in the data bus;

[0028] According to the device interface coding, the vehicle networking static account data and the vehicle networking measurement data are associated and mapped, measurement points and measurement point information are generated for the vehicle networking measurement data according to the association and mapping result, and the measurement points and measurement point information are stored in the resource measurement measurement point table; the measurement point information includes resource ID;

[0029] Only when the association and mapping result is successful, the corresponding resource information expansion measurement point information is obtained from the vehicle networking static account data; and the resource ID in the resource information is used to generate measurement points and measurement point information for the vehicle networking measurement data;

[0030] When the association and mapping result is failed, the device interface coding is used to generate measurement points and measurement point information for the vehicle networking measurement data.

[0031] Further, the step of associating and mapping the Internet of Vehicles static account data and the Internet of Vehicles measurement data according to the device interface code specifically comprises:

[0032] For each piece of Internet of Vehicles measurement data, the device interface code is taken out and spliced with the IOVPSR field to generate a PSR ID field;

[0033] In the Internet of Vehicles static account data, a record with the same resource ID and PSR ID field is queried, and if the Internet of Vehicles static account data can be queried, it indicates that the association is successful, otherwise it indicates that the association fails.

[0034] Further, the step of generating a standard collection queue according to the measurement point and the measurement point information specifically comprises:

[0035] The measurement point information comprises a network province code;

[0036] According to the measurement point and the network province code, a standard collection queue is generated for each network province, and the standard collection queue comprises an Internet of Vehicles charging gun measurement ID collection queue, an Internet of Vehicles charging gun telemetry collection queue, an Internet of Vehicles charging gun telesignaling collection queue, an Internet of Vehicles charging gun signal event collection queue and an Internet of Vehicles charging gun management type event collection queue.

[0037] Further, the step of accessing the Internet of Vehicles measurement data by consuming the Internet of Vehicles measurement data in the standard collection queue specifically comprises:

[0038] Data in the Internet of Vehicles charging gun measurement ID collection queue is written into a resource measurement measurement point table;

[0039] According to the measurement type, for data in the Internet of Vehicles charging gun telemetry collection queue, the data corresponding to the successful association is written into an Internet of Vehicles telemetry voltage table, an Internet of Vehicles telemetry current table and an Internet of Vehicles power table; and the data corresponding to the failed association is written into an Internet of Vehicles telemetry unassociated table, an Internet of Vehicles power unassociated table and a measurement unassociated table;

[0040] According to the data time, the data in the Internet of Vehicles charging gun telesignaling collection queue is divided into real-time data and section data, the section data corresponding to the successful association is stored in an Internet of Vehicles section telesignaling table, and the data corresponding to the failed association is stored in an Internet of Vehicles section telesignaling unassociated table and a measurement unassociated table;

[0041] Data in the Internet of Vehicles charging gun signal event collection queue is stored in a signal event table for power collection;

[0042] Data in the Internet of Vehicles charging gun management type event collection queue is stored in a management type event table.

[0043] In a second aspect, the present application provides an electronic device, which comprises:

[0044] at least one processor;

[0045] and a memory connected in communication with the at least one processor;

[0046] 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 perform a vehicle networking measurement data access method.

[0047] In a third aspect, the present application provides a computer readable storage medium storing computer instructions for enabling a processor to implement a vehicle networking measurement data access method when executed.

[0048] In a fourth aspect, the present application provides a computer program product comprising a computer program for implementing a vehicle networking measurement data access method when executed by a processor.

[0049] Beneficial effects: The present application receives the charging gun telemetry, remote signaling and event data pushed by the vehicle networking system in real time, forms vehicle networking measurement data and pushes to the message queue storage; writes the vehicle networking measurement data into the intermediate library and then transmits to the data bus; associates and maps the vehicle networking measurement data with the vehicle networking account data of the power grid resource business center, generates a measurement point and stores into the database; parses and converts the vehicle networking measurement data stream in the data bus, generates a standard collection queue according to the measurement point information; establishes a vehicle networking measurement data table, and the headquarters and each network and provincial company consume the vehicle networking measurement data in the standard collection queue and store to the vehicle networking measurement data table. By adopting the above technical scheme, compared with the prior art, the present application has the following advantages:

[0050] (1) The present application realizes stable transmission and real-time forwarding of vehicle networking measurement data: on the one hand, high-concurrency stable transmission, under the condition of high throughput of source data, realizes reliable transmission of vehicle networking data from the external network to the Internet area and then to the management information area; on the other hand, real-time forwarding, realizes real-time forwarding of vehicle networking data from the intermediate library to the data bus, and guarantees the timeliness of data collection and aggregation.

[0051] (2) The present application realizes accurate association and real-time calculation of vehicle networking measurement data: on the one hand, the association with the account data generates a measurement point, which can be associated and matched with the vehicle networking account data of the power grid resource business center and generate a measurement point, and the measurement point is stored into the database; on the other hand, data stream real-time calculation, based on mapping, filtering, grouping and adaptation and other data conversion methods, generates a standard collection queue on the data bus, which is consumed by the headquarters and the provincial side and written into the corresponding vehicle networking measurement data table.

[0052] (3) This invention enables real-time analysis and processing of vehicle network measurement data at the headquarters and provincial levels, as well as persistent storage.

[0053] (4) This invention enables effective data analysis and display: Based on the access vehicle network measurement data, it can support the display of equipment parameters, operating status and other information of charging station pile guns on platforms such as power grid map and calculation simulation, and perform power flow calculation, power consumption analysis, charging scale statistics, power quality monitoring and charging cost statistics, realize the lean management of charging equipment power consumption business, realize the layout optimization of charging network, and realize the real-time dynamic presentation of physical vehicle network in digital space. Attached Figure Description

[0054] Figure 1 This is a flowchart illustrating a method for accessing vehicle network measurement data according to an embodiment of the present invention.

[0055] Figure 2 This is a schematic diagram illustrating the process of receiving and pushing vehicle network data according to an embodiment of the present invention;

[0056] Figure 3 This is a schematic diagram of the measurement data transmission process provided in an embodiment of the present invention;

[0057] Figure 4 This is a schematic diagram illustrating the process of ledger association and measurement point generation provided in an embodiment of the present invention;

[0058] Figure 5 This is a schematic diagram illustrating the process of generating a standard data acquisition queue, as provided in an embodiment of the present invention.

[0059] Figure 6 This is a schematic diagram of the standard data collection queue consumption and storage process provided in an embodiment of the present invention. Detailed Implementation

[0060] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will further describe the vehicle network measurement data access method and system proposed by the present invention in conjunction with the accompanying drawings and embodiments.

[0061] like Figure 1 As shown, this embodiment of the invention provides a method for accessing vehicle network measurement data, specifically including the following steps:

[0062] Step 1: Receive telemetry, telesignaling, and event data of the charging gun pushed by the vehicle network system in real time through load balancing and peak shaving and valley filling technologies, form vehicle network measurement data, and push it to the message queue for storage.

[0063] The specific implementation process of step 1 is as follows:

[0064] S101, the Internet of Vehicles system calls a data receiving service interface, pushes the charging state telemetry data, charging equipment state change telesign data and charging order event data of the charging gun, and forms Internet of Vehicles measurement data;

[0065] S102, deploy a data receiving service on a cloud server, configure an Nginx load balancing service, use multiple nodes to receive high-throughput Internet of Vehicles measurement data of the Internet of Vehicles system, reduce the pressure caused by large data concurrency on the cluster, and realize the transmission of Internet of Vehicles measurement data from the Internet to the company's Internet area;The Nginx load balancing service can be specifically understood as: a technology that distributes Internet of Vehicles measurement data to multiple servers to optimize resource use, improve system performance and availability.

[0066] S103, the data receiving service pushes the received Internet of Vehicles measurement data to the corresponding Topic of the RocketMQ message queue for storage, and realizes traffic peak shaving. RocketMQ message queue can be specifically understood as: a distributed message middleware, mainly used to solve application decoupling, asynchronous processing, traffic peak shaving and other problems in distributed systems, suitable for high concurrency and high reliability scenarios. Topic can be specifically understood as: a top-level container in RocketMQ used to identify message transmission and storage, which is uniquely identified and distinguished by TopicName. Each Topic can contain multiple message queues (MessageQueue), which are the actual storage units of messages, responsible for physical storage and distributed management of messages.

[0067] Figure 2 The above process is shown in a simplified flowchart.

[0068] The embodiment of the application configures a load balancing strategy on Nginx, uses multiple nodes to receive the Internet of Vehicles measurement data pushed by the Internet of Vehicles system, and ensures the stability of the Internet of Vehicles measurement data reception. And store the data in the RocketMQ message queue, use multiple message queues to store these concurrent requests, ensure the stability and continuity of the service, realize the push of Internet of Vehicles measurement data from the Internet to the Internet area.

[0069] Taking the Internet of Vehicles system platform developed by State Grid Wisdom Internet of Vehicles Technology Co., Ltd. as an example, step 1 is further described. Specifically, it includes:

[0070] The charging state telemetry data of the charging gun includes: being pushed once every 3 minutes in the charging state, and being composed of attributes such as a charging order number, a charging order state, a charging device interface code, a charging device interface state, an A-phase current, a B-phase current, a C-phase current, a direct current, an A-phase voltage, a B-phase voltage, a C-phase voltage, a direct current voltage, an active power, a reactive power, a battery remaining capacity, a start charging time, a current sampling time, a cumulative charging amount, a cumulative electricity fee, a cumulative service fee and a cumulative total amount.

[0071] The charging device state change remote signaling data is divided into a section state and a real-time change state, the section state is pushed once every 2 hours, the real-time change state is pushed once immediately, and is composed of attributes such as a charging device interface code, a charging device interface state, a parking space state, a ground lock state and an update time.

[0072] The charging order event data includes: being pushed once at the start and end of charging, and being composed of attributes such as a charging order number, a charging device interface code, a start charging time, an end charging time, a cumulative charging amount, a total electricity fee, a total service fee, a cumulative total amount, a vehicle identification code and a charging end reason.

[0073] The telemetry, remote signaling and event data of the charging gun are associated through the device interface code to obtain the complete charging state, device state change and charging order information of the charging gun. After being associated with the static account data of the power grid resource business middle station, the resource information of the charging station, charging pile and charging gun can be obtained. The source end device ID recorded in the measurement center is the device code ID of the data pushed by the source end system, which is the charging device interface code for the Internet of Vehicles, and is simply referred to as the device interface code in the embodiment.

[0074] Step 2: Based on the isolation penetration technology, the Internet of Vehicles measurement data stored in the message queue is written into the intermediate library, and then through the data transmission cloud service component, the Internet of Vehicles measurement data is transmitted from the intermediate library to the data bus, and the Internet of Vehicles measurement data forms an Internet of Vehicles measurement data stream in the data bus.

[0075] The RocketMQ message queue is in the Internet area, and the measurement center to be accessed is in the management information area, and the two are protected by an isolation device, and the characteristics of the isolation device only allow the Internet area to access the management information area in the form of SQL penetration. Therefore, the Internet of Vehicles measurement data stored in the message queue needs to be transmitted to the data bus of the measurement center through the isolation device. The SQL can be understood as a kind of database language.

[0076] The specific implementation process of step 2 is as follows:

[0077] S201, the data push service consumes the Internet of Vehicles measurement data stored in the RocketMQ message queue according to the name of the Topic, penetrates the information security network isolation device, parses the Internet of Vehicles measurement data, and writes the Internet of Vehicles measurement data into the corresponding data table of the RDS intermediate library, so that the transmission of the Internet of Vehicles measurement data from the Internet area to the management information area is realized.

[0078] S202, the DTS data transmission service is used to synchronize the Internet of Vehicles measurement data in the corresponding data table of the RDS intermediate library to the Datahub data bus, each data table corresponds to a Topic of the Datahub data bus, and the data table structure is the same as the Topic structure.

[0079] S203, the data and logs synchronized to the Datahub data bus are deleted in a time manner, so that the performance of database query is ensured.

[0080] Figure 3 A simplified flowchart of the above process is shown.

[0081] The embodiment of the application deploys a data push service in the Internet area, and consumes the Topic of the charging state, the charging equipment state change and the charging order from the RocketMQ message queue. An RDS intermediate library is created in the management information area, and is used to store the Internet of Vehicles measurement data. The data push service penetrates the isolation device, and writes the Internet of Vehicles measurement data into the data table of the charging state, the charging equipment state change and the charging order of the RDS intermediate library, so that the transmission of the data from the Internet area to the management information area is realized. In addition, the DTS data transmission service is used to synchronize the table data of the RDS intermediate library to the Datahub data bus, each data table of the RDS database corresponds to a Topic of the Datahub data bus, and the data table structure is the same as the Topic structure, so that the integrity and consistency of the data transmission are ensured.

[0082] It should be noted that, since the Internet of Vehicles measurement data throughput is large, the data and logs of the RDS intermediate library also grow very fast, and the storage space is occupied very much. In order to ensure the normal operation and performance of the database, the data push service will delete the RDS intermediate library data and the corresponding logs synchronized to the Datahub data bus in a time manner.

[0083] Step 3: according to the Spark scanning and the measurement point generation algorithm, the Internet of Vehicles measurement data in the data bus is associated and mapped with the Internet of Vehicles account data of the power grid resource business platform, a measurement point is generated, and is stored in the database.

[0084] The specific implementation process of step 3 is as follows:

[0085] S301, deploy a Spark scheduling task on a Dataworks platform to scan the Internet of Vehicles static account data of the power grid resource business middle platform and the Internet of Vehicles measurement data in the data bus; the DataWorks platform can be specifically understood as: a platform integrating data development, scheduling and operation and maintenance, supporting various big data processing tasks, including scheduling and execution of Spark jobs.

[0086] S302, according to the device interface code, the Internet of Vehicles static account data and the Internet of Vehicles measurement data are associated and mapped, the measurement point and the measurement point information are generated according to the association and mapping result of the Internet of Vehicles measurement data, and the generated measurement point and measurement point information are stored in the resource measurement measurement point table. The measurement point is a field of measurement ID (MEASUREMENT_ID), and the measurement point information is a record of the entire measurement point table. The association is successful, and the measurement point information is obtained. Writing the generated measurement point information is more accurate.

[0087] Figure 4 The simplified process of the above process is shown.

[0088] The Internet of Vehicles measurement data can be specifically understood as voltage, current and power and other observable and measurable controllable data; the Internet of Vehicles static account data can be specifically understood as device information such as resource ID, asset ID, operation and maintenance manufacturer, factory date, etc. Only the association of the two can obtain all the fields required for generating measurement points. All the fields required for the measurement point can be specifically understood as: resource ID, network and province code, measurement type and other resource information generated according to the measurement ID generation algorithm.

[0089] In the embodiment of the application, the specific implementation process of step S302 is as follows:

[0090] S3021, for the unassociated data of the Internet of Vehicles static account data and the Internet of Vehicles measurement data, the device interface code is used for association and mapping, if the association is successful, the resource information of the charging gun is obtained, the resource information includes but is not limited to resource ID and network and province code and other information; if the association fails, the resource information of the charging gun cannot be expanded.

[0091] In the embodiment of the present application, in order to accurately associate the vehicle networking static account data of the vehicle networking measurement data and the power grid resource business center, the Spark scheduling task is deployed on the Dataworks platform to scan the vehicle networking static account data of the power grid resource business center and the vehicle networking measurement data of the real-time measurement center. Specifically, for each vehicle networking measurement data, the device interface code is taken out and the "IOVPSR" field is spliced to generate the PSR_ID field; the generated PSR_ID field is used for association mapping, which specifically includes: querying the record with the same resource ID and PSR_ID field in the vehicle networking static account data, and successfully querying the vehicle networking static account data to obtain the resource ID and network province code of the vehicle networking measurement data, which indicates that the association is successful, and the resource ID and network province code of the charging gun and other resource information are obtained; if the association fails, the resource information of the charging gun cannot be expanded. The network province code can be understood as: used to identify which network province this data belongs to, so as to divide the standard collection queue.

[0092] S3022, if the association is successful, the resource ID of the charging gun is used to generate the measurement point and measurement point information for the vehicle networking measurement data; if the association fails, the device interface code is used to generate the measurement point and measurement point information for the vehicle networking measurement data.

[0093] S3023, the generated measurement point and measurement point information are stored in the resource measurement measurement point table, and the vehicle networking measurement data associated successfully is deleted from the measurement unassociated table. The measurement point information is the resource ID and network province code of the corresponding vehicle networking measurement data.

[0094] S3024, the Spark scheduling task scans the resource measurement measurement point table to query whether the generated measurement point exists, if it exists, it is not generated repeatedly; if the vehicle networking measurement data not associated successfully previously is associated successfully with the vehicle networking static account data later, the measurement point and measurement point information in the resource measurement measurement point table are updated.

[0095] It should be noted that the resource ID and network province code and other resource information do not exist in the vehicle networking measurement data of the real-time measurement center, and need to be associated with the vehicle networking static account data of the power grid resource business center to obtain the standard collection queue of each network province according to the network province code.

[0096] Step 4: based on the real-time computing engine, the vehicle networking measurement data flow in the data bus is parsed and converted, and the standard collection queue is generated according to the measurement point.

[0097] The specific implementation process of step 4 is as follows:

[0098] S401, based on the real-time computing engine, the vehicle networking measurement data flow in the Datahub data bus is parsed and converted.

[0099] S402, after the vehicle networking measurement data stream is parsed and converted, a standard collection queue Topic is generated according to the measurement points and measurement point information, and the standard collection queue Topic includes vehicle networking charging gun measurement ID, vehicle networking charging gun telemetry, vehicle networking charging gun telematics, vehicle networking charging gun signal event and vehicle networking charging gun management type event.

[0100] Figure 5 The simplified flow of the above process is shown.

[0101] It should be noted that the vehicle networking measurement data access is for sharing service application, promoting the development of vehicle network integration, and making up for the defects that the current charging and battery replacement equipment cannot be connected to the power grid. In addition, the measurement data can be uploaded to the power grid map system, and the measurement data is displayed on the power grid map system, which is convenient for visualization and statistical analysis, and can also be based on measurement data for power consumption analysis and calculation deduction and other businesses. Therefore, the measurement data must be stored according to different types, so as to be called by other applications.

[0102] It should be noted that the key attribute of the standard collection queue is the measurement point, and the standard collection queue is generated for each network province according to the measurement point, resource ID and network province code. The standard collection queue Topic includes: vehicle networking charging gun measurement ID, vehicle networking charging gun telemetry, vehicle networking charging gun telematics, vehicle networking charging gun signal event and vehicle networking charging gun management type event. The headquarters also has a standard collection queue, and each Topic of the headquarters contains the data of all the corresponding Topics of the network provinces.

[0103] In the embodiment of the application, the specific implementation process of S401 is as follows:

[0104] S4011, deploying a Blink task to consume the Topic data of the charging state telemetry data, charging equipment state change telematics data and charging order event data of the charging gun;

[0105] S4012, performing operator operations such as parsing, adapting and converting on the vehicle networking measurement data stream;

[0106] S4013, performing field legal verification on the processed vehicle networking measurement data stream, and transporting the vehicle networking measurement data stream that passes the verification to the downstream according to the device interface code;

[0107] The purpose of S4012 and S4013 is to preliminarily parse and check the vehicle networking measurement data in the data bus and then continue to output the data stream. The subsequent association and warehousing steps are all based on the data stream after the preliminary processing of S4012 and S4013.

[0108] S4014, taking out the measurement points and measurement point information of the resource measurement measurement point table and storing them in the Redis cache.

[0109] S4015, based on the "IOVPSR" field and the device interface code, the Internet of Vehicles measurement data stream is associated with the measurement point information of the Redis cache; if the association is successful, it is further judged whether the resource ID and the network province code are empty; if they are empty, the side stream is output to the measurement unassociated Topic; if they are not empty, the resource ID and the network province code are expanded to expand the fields of the Internet of Vehicles measurement data stream, and the network province code and the measurement type field are output to the standard collection queue according to the network province code and the measurement type field, for example, the measurement type of the Internet of Vehicles measurement data stream is "A-phase voltage", and the network province code is "Jiangsu", so the Internet of Vehicles charging gun telemetry Topic in the standard collection queue of Jiangsu is output to the side stream; if the association is not successful, the side stream is output to the measurement unassociated Topic.

[0110] Step 5, the Internet of Vehicles measurement data table is established, and the Blink task is deployed in the measurement center of the headquarters and the network province company, the Internet of Vehicles measurement data in the standard collection queue is consumed, and parsing, adaptation, conversion and statistics are performed, and finally the Internet of Vehicles measurement data is stored in the Internet of Vehicles measurement data table.

[0111] The specific implementation process of step 5 is as follows:

[0112] S501, the charging state telemetry data of the accessed charging gun, the charging device state change telesign data and the charging order event data are used to establish the Internet of Vehicles measurement data table.

[0113] The Internet of Vehicles measurement data table includes the Internet of Vehicles telemetry current table, the Internet of Vehicles telemetry voltage table, the Internet of Vehicles telemetry other table, the Internet of Vehicles telemetry unassociated table, the Internet of Vehicles section telesign table, the Internet of Vehicles section telesign unassociated table, the Internet of Vehicles power table, the Internet of Vehicles power unassociated table, the power signal event table, and the power management event table. Among them, the power signal event table and the power management event table are PG data tables, and the other tables are HBase data tables.

[0114] S502, the headquarters side deploys a Blink task to consume all the Internet of Vehicles measurement data of the standard collection queue Topic, performs data conversion and adaptation, and writes the data into the Internet of Vehicles measurement data table of the headquarters real-time measurement center.

[0115] S503, each network province deploys a Blink task to consume the standard collection queue Topic data of the province from the headquarters Datahub data bus, performs data conversion and adaptation, and writes the data into the Internet of Vehicles measurement data table of the real-time measurement center of the province.

[0116] Figure 6 The simplified flowchart of the above process is shown.

[0117] In the embodiment of the application, S502 specifically includes the following steps:

[0118] S5021, the headquarters side deploys a Blink task to consume vehicle networking measurement ID data Topic, and writes in a resource measurement measuring point table;

[0119] S5022, the headquarters side deploys a Blink task to consume vehicle networking charging gun telemetry data Topic, and is divided into A-phase voltage, A-phase current, B-phase voltage, B-phase current, C-phase voltage, C-phase current, DC voltage, DC current, cumulative charging quantity and the like according to the measurement type. The voltage data associated successfully is written in a vehicle networking telemetry voltage table, the current data associated successfully is written in a vehicle networking telemetry current table, and the electric quantity data associated successfully is written in a vehicle networking electric quantity table; the voltage and current data associated unsuccessfully are written in a vehicle networking telemetry unassociated table; the electric quantity data associated unsuccessfully is written in a vehicle networking electric quantity unassociated table; and other unassociated successfully data is written in a measurement unassociated table;

[0120] S5023, the headquarters side deploys a Blink task to consume vehicle networking charging gun remote signaling data Topic, and is divided into real-time and section data according to data time, the section data associated successfully is stored in a vehicle networking section remote signaling table, and the data associated unsuccessfully is stored in a vehicle networking section remote signaling unassociated table and a measurement unassociated table;

[0121] S5024, the headquarters side deploys a Blink task to consume vehicle networking charging gun signal event data Topic, and stores in a signal event table for power collection regardless of whether association is successful or not;

[0122] S5025, the headquarters side deploys a Blink task to consume vehicle networking charging gun management type event data Topic, and stores in a management type event table regardless of whether association is successful or not.

[0123] In the embodiment of the application, S503 specifically comprises the following steps:

[0124] S5031, the network province side deploys a Blink task to consume vehicle networking measurement ID data Topic, and writes in a resource measurement measuring point table;

[0125] S5032, the network province side deploys a Blink task to consume vehicle networking charging gun telemetry data Topic, and is divided into A-phase voltage, A-phase current, B-phase voltage, B-phase current, C-phase voltage, C-phase current, DC voltage, DC current, cumulative charging quantity and the like according to the measurement type. Voltage data is written in a vehicle networking telemetry voltage table, current data is written in a vehicle networking telemetry current table, and electric quantity data is written in a vehicle networking electric quantity table;

[0126] S5033, the network province side deploys a Blink task to consume vehicle networking charging gun remote signaling data Topic, and is divided into real-time and section data according to data time, and section data is stored in a vehicle networking section remote signaling table;

[0127] S5034, the network side deploys a Blink task to consume the vehicle networking charging gun signal event data Topic, and stores it in a signal event table for power collection;

[0128] S5035, the network side deploys a Blink task to consume the vehicle networking charging gun management event data Topic, and stores it in a management event table.

[0129] The embodiment of the application realizes smooth reception and real-time forwarding of vehicle networking measurement data by receiving vehicle networking system data, pushing and transmitting measurement data, associating account books and generating measurement points, analyzing and calculating data flow, generating a standard collection queue, consuming messages and storing them in a database, realizing the interconnection and association matching of vehicle networking measurement data and middle station account book data, and realizing real-time analysis and processing and persistent storage of headquarters and network side vehicle networking measurement data. The method can improve the panoramic observation and analysis capability of new energy vehicle charging load, make the charging station pile gun data efficiently and accurately connected to the power grid, fully support the power grid charging and battery swapping load monitoring and characteristic analysis, can predict operation and management risks and tap the adjustable capacity of the distribution network, guide the power grid to carry out reasonable capacity expansion and network construction, and promote the development of vehicle network integration business.

[0130] The embodiment of the application is based on cloud native architecture, and through load balancing, message queue and big data technology, telemetry, remote signaling and event data of charging station piles and guns are accessed from the vehicle networking platform, the measurement data is analyzed, checked and converted, and is transmitted and stored to the headquarters in real time. Each network province company consumes and stores the provincial vehicle networking measurement data from the headquarters. The system covers three major technical innovation systems, and realizes the full-link technical breakthrough of vehicle networking data "collection, transmission, storage and use". A high-concurrency transmission scheme of "load balancing + message queue" is proposed, a measurement point generation algorithm of "cache preloading + batch association" is innovatively designed, and a standardized service system of "multi-dimensional data model + standard collection queue" is constructed. The problems of real-time transmission of massive vehicle network interaction data, multi-dimensional vehicle networking data association and large-scale load data collection, transmission, storage and use management are solved. The system accesses data covering about 219,000 charging guns, 168,000 charging piles and 47,000 charging stations; daily data processing is 0.5 billion, and storage is about 0.1 TB. The system supports 12 business applications such as power grid map load monitoring and PMS3.0 power analysis, saves operation and maintenance labor cost, optimizes power grid capacity decision, and improves the economic benefit of orderly charging. Compared with the traditional method, the data transmission delay is reduced by 51%, the account association time is reduced by 93%, the storage cost is reduced by 80%, and the measurement point generation efficiency is improved by 64%.

Claims

1. A method for accessing vehicle network measurement data, characterized in that: include: Real-time vehicle network measurement data is stored in the data bus; The vehicle network measurement data in the data bus is parsed and transformed in real time, and the parsed and transformed vehicle network measurement data is classified and stored in the standard acquisition queue according to different types; By collecting vehicle network measurement data from the consumer standard collection queue, the access to vehicle network measurement data is achieved; The standard acquisition queue is generated according to the following steps: The vehicle network measurement data and the vehicle network static ledger data are correlated and mapped to obtain the correlation mapping results; Based on the correlation mapping results, measurement points and measurement point information are generated for the vehicle network measurement data. A standard data acquisition queue is generated based on the measurement points and their information. 2.The method of claim 1, wherein: The aforementioned storage of real-time vehicle network measurement data into the data bus specifically includes: Message queues are used to store real-time vehicle network measurement data; The vehicle network measurement data in the message queue is parsed and written to the corresponding data tables in the intermediate database deployed in the management information area; according to the measurement data type, the vehicle network measurement data in the message queue corresponds one-to-one with the data tables in the intermediate database; The vehicle network measurement data in the intermediate database data table is synchronized to the data bus. 3.The method of claim 2, wherein: The vehicle network measurement data includes: charging status telemetry data of the charging gun, charging equipment status change telemetry data of the charging gun, and charging order event data of the charging gun; the charging status telemetry data of the charging gun, the charging equipment status change telemetry data of the charging gun, and the charging order event data of the charging gun are associated through device interface coding. Correspondingly, the intermediate database includes the following data tables: charging status data table for charging guns, charging device status change data table for charging guns, and charging order event data table for charging guns. 4.The method of claim 2, wherein: The aforementioned use of message queues to store real-time vehicle network measurement data specifically includes: Acquire vehicle-to-everything (V2X) measurement data; Using Nginx load balancing and peak shaving services, vehicle network measurement data is pushed to a RocketMQ message queue for storage. 5.The method of claim 3, wherein: The process involves mapping the vehicle network measurement data with the vehicle network static ledger data to obtain the mapping result. Based on the association mapping results, measurement points and measurement point information are generated for the vehicle-to-everything (V2X) measurement data, specifically including: Scan the vehicle network static ledger data and vehicle network measurement data in the data bus of the power grid resource business platform; The vehicle network static ledger data and vehicle network measurement data are associated and mapped according to the device interface code. Based on the association mapping result, measurement points and measurement point information are generated for the vehicle network measurement data, and the measurement points and measurement point information are stored in the resource measurement measurement point table; the measurement point information includes resource ID; Only when the association mapping result is successful will the corresponding resource information be obtained from the vehicle network static ledger data to expand the measurement point information; and the resource ID in the resource information will be used to generate measurement points and measurement point information for the vehicle network measurement data. When the association mapping result is that the association fails, the device interface encoding is used to generate measurement points and measurement point information for the vehicle network measurement data.

6. The method of claim 5, wherein: The aforementioned association mapping between vehicle network static ledger data and vehicle network measurement data based on device interface codes specifically includes: For each vehicle networking measurement data, the device interface code is taken out and spliced with the IOVPSR field to generate the PSR_ID field; In the vehicle networking static account data, a record with the same resource ID and PSR_ID field is queried. If the vehicle networking static account data can be queried, it indicates that the association is successful, otherwise it indicates that the association fails.

7. The method of claim 5, wherein: The standard collection queue is generated according to the measuring point and the measuring point information, and specifically includes: The measuring point information includes the network province code; According to the measuring point and the network province code, a standard collection queue is generated for each network province, which includes: vehicle networking charging gun measurement ID collection queue, vehicle networking charging gun telemetry collection queue, vehicle networking charging gun telesignaling collection queue, vehicle networking charging gun signal event collection queue and vehicle networking charging gun management type event collection queue. 8.The method of claim 7, wherein: The vehicle networking measurement data is accessed by consuming the vehicle networking measurement data in the standard collection queue, and specifically includes: Data in the vehicle networking charging gun measurement ID collection queue is written into the resource measurement measuring point table; According to the measurement type, for the data in the vehicle networking charging gun telemetry collection queue, the successfully associated data is written into the vehicle networking telemetry voltage table, the vehicle networking telemetry current table and the vehicle networking power table; the unsuccessfully associated data is written into the vehicle networking telemetry unassociated table, the vehicle networking power unassociated table and the measurement unassociated table; According to the data time, the data in the vehicle networking charging gun telesignaling collection queue is divided into real-time data and section data, the successfully associated section data is stored in the vehicle networking section telesignaling table, and the unsuccessfully associated data is stored in the vehicle networking section telesignaling unassociated table and the measurement unassociated table; Data in the vehicle networking charging gun signal event collection queue is stored in the signal event table for power collection; Data in the vehicle networking charging gun management type event collection queue is stored in the management type event table.

9. An electronic device, comprising: The electronic device includes: At least one processor; And a memory connected in communication with the at least one processor; 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 vehicle networking measurement data access method of any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to enable the processor to execute the vehicle networking measurement data access method of any one of claims 1-8 when executed.

11. A computer program product, characterised in that, The computer program product includes a computer program, and the computer program implements the vehicle networking measurement data access method of any one of claims 1-8 when executed by the processor.

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