Method and system for monitoring operation state of power collection full link, medium and terminal

Abstract

The application discloses a kind of monitoring method and system for collecting full-link operation state of electricity, medium, terminal, it is related to power system data acquisition technical field, main purpose is to improve the problem that due to unable full-link tracking, leading to full-link operation state cannot be fine monitoring, and due to unable accurate positioning specific link where exception occurs, leading to low efficiency of abnormal positioning problem. By constructing the time tag system of electricity information acquisition protocol covering the full-link of electricity collection, full-link timestamp tracking is realized, so that the full-link operation state can be fine monitoring;At the same time, by real-time processing link, the overall real-time monitoring result is quickly output, to realize overall real-time monitoring, and by offline analysis link, segmented link data analysis is carried out, segmented link data statistics chart is generated, to directly locate specific link where exception occurs from statistics chart, without relying on business end backtracking investigation, improve the efficiency and accuracy of abnormal positioning.

Description

Technical Field

[0001] This application relates to the field of power system data acquisition technology, and in particular to a method, system, medium, and terminal for monitoring the operational status of the entire power consumption acquisition chain. Background Technology

[0002] With the continuous improvement of the digitalization and intelligence level of the power system, the electricity consumption information acquisition system, as the core infrastructure of the main entry point for sensing data and the main exit point for control commands, has been widely used in key business scenarios such as user demand response, distribution network outage repair, orderly electricity consumption, and distributed photovoltaic monitoring. Currently, the electricity consumption information acquisition system is gradually developing towards high concurrency, multi-protocol, and end-to-end controllability, which puts forward higher requirements for the real-time performance, accuracy, and transparency of the operational status of the acquired data.

[0003] In existing technologies, electricity information collection systems typically interact with electricity meters via concentrators, and the collection tasks are uniformly scheduled and managed through a master station system. To ensure the controllability of data collection, some systems have established a basic communication link monitoring mechanism between the master station and the concentrator, which can record the completion status of task issuance and data reporting.

[0004] However, on the one hand, due to the lack of unified observation methods for the operation status of various links in the data acquisition chain, such as the main station, communication channel, concentrator and electricity meter, it is difficult to achieve full-link tracking from the issuance of acquisition instructions to data feedback, resulting in the inability to monitor the operation status of the entire link in a refined manner; on the other hand, when data acquisition is abnormal or delayed, the existing methods mostly rely on the business side to reverse the investigation, which cannot accurately locate the specific link where the abnormality occurred, resulting in low efficiency in abnormality location. Summary of the Invention

[0005] In view of this, this application provides a method, system, medium, and terminal for monitoring the operational status of the entire power consumption acquisition link. The main purpose is to improve the problem that the lack of unified observation methods for the operational status of each link in the acquisition link makes it difficult to achieve full-link tracking, resulting in the inability to monitor the operational status of the entire link in a refined manner. Furthermore, when abnormalities or delays occur in the acquisition, existing methods often rely on reverse investigation from the business side, which cannot accurately locate the specific link where the abnormality occurred, resulting in low efficiency in abnormality location.

[0006] According to one aspect of this application, a method for monitoring the operational status of the entire power consumption data acquisition chain is provided, comprising: The electricity consumption information collection protocol is expanded based on the target standard specification documents, and a time tag system for the electricity consumption information collection protocol is constructed, wherein the time tag system for the electricity consumption information collection protocol contains multiple time tags; The data acquisition front-end module parses the timestamp data recorded by the acquisition terminal routing application, extracts the timestamp data corresponding to each time tag from the timestamp data, and forwards the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset timestamp and the message queue topic. Subscribe to message queue topics that are mapped to pre-built real-time processing links, and based on the timestamp data in the message queue topics that are mapped to the pre-built real-time processing links, use the real-time processing links to perform overall real-time monitoring of the entire power consumption acquisition link operation status, and generate overall real-time monitoring results. Also, subscribe to all the message queue topics, and based on the timestamp data in all the message queue topics, use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the entire power consumption acquisition link operation status, and generate segmented link data statistical charts.

[0007] Preferably, the step of parsing the timestamp data recorded by the acquisition terminal routing application through the acquisition front-end module, extracting the timestamp data corresponding to each time tag from the timestamp data, and forwarding the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between preset timestamps and message queue topics includes: The acquisition front-end module loads a protocol plugin that supports the electricity consumption information acquisition protocol time tag system; Based on the protocol plugin, the extended protocol message reported by the routing application of the acquisition terminal is received, the time tags in the extended protocol message are parsed and processed to extract the timestamp data corresponding to each time tag, and the full set of timestamp data is standardized to generate multiple standardized intermediate data. Multiple standardized intermediate data are pushed to the adapted data routing module, so that the adapted data routing module forwards each standardized intermediate data to the corresponding message queue topic based on the mapping relationship between the preset time tag and the message queue topic.

[0008] Preferably, before standardizing the entire set of timestamp data to generate multiple standardized intermediate data, the method further includes: For each timestamp data, a preset clock deviation between the acquisition terminal used to collect the current timestamp data and the main station is obtained, and the current timestamp data is corrected based on the preset clock deviation to generate corrected timestamp data, and then the corrected timestamp data is standardized.

[0009] Preferably, the subscription has a mapping relationship with the pre-built real-time processing link of the message queue topics, and based on the timestamp data in the mapped message queue topics, the real-time processing link is used to perform overall real-time monitoring of the entire power consumption collection link operation status, generating overall real-time monitoring results, including: Subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link; Extract the timestamps of the concentrator receiving the main station's collection request, the concentrator's collection start time, and the concentrator's collection completion time from the message queue topics that have a mapping relationship with the real-time processing link; Based on the timestamp of the concentrator receiving the main station's collection request, the timestamp of the concentrator starting collection, and the timestamp of the concentrator completing collection, the total end-to-end time and total end-to-end delay of each real-time power consumption collection record are calculated, and the total end-to-end time and total end-to-end delay are mapped to the real-time power consumption collection record and written into the real-time processing link database. In the real-time processing link database, real-time power consumption collection records with a total total time exceeding a preset threshold and a total delay exceeding a preset threshold are filtered out and output as abnormal alarm information to monitor the overall real-time operation status of the entire power consumption collection link.

[0010] Preferably, the subscription involves all message queue topics, and based on the timestamp data in all message queue topics, segmented data analysis of the entire power consumption data collection process is performed using a pre-built offline analysis link from the previous monitoring period, generating segmented data statistical charts, including: Subscribe to all the aforementioned message queue topics through the ingestion process; The timestamp data in each of the aforementioned message queue topics are categorized by message queue topic and written into a persistent database for storage; From the persistent database, obtain the full timestamp data of each historical electricity consumption collection record from the previous monitoring period; Based on the full timestamp data, calculate the total end-to-end time, total end-to-end delay, and segmented time data for each of the historical electricity consumption collection records; A basic analysis wide table is generated based on all the historical electricity consumption records and the corresponding total end-to-end time, total end-to-end delay, and segmented link time data. Based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption collection process to generate segmented data statistical charts. These charts include full-link data statistical charts based on business and regional distribution area dimensions, as well as statistical charts showing the percentage of abnormalities in each segment under different abnormal link status types.

[0011] Preferably, based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption data acquisition process to generate full-link data statistical charts at both the business and regional distribution area levels, including: For each regional transformer area, the number of historical power consumption collection records in the current regional transformer area whose total end-to-end time exceeds the preset total end-to-end time threshold is counted from the basic analysis wide table. The proportion of the number of historical power consumption collection records that timed out to the total number of historical power consumption collection records in the current regional transformer area is calculated to obtain the abnormality rate of the current regional transformer area. Based on each of the aforementioned anomaly rates, a color level is configured for the corresponding regional transformer area, wherein the color level is proportional to the anomaly rate; For each regional transformer station, locate the geographical area of ​​the current regional transformer station on the electronic map, and render the geographical area according to the color level corresponding to the current regional transformer station to generate a full-link data statistical chart at the regional transformer station dimension; Furthermore, for each business type, multiple historical electricity consumption data collection records included in the current business type are obtained from the basic analysis wide table. These records are then grouped according to a preset statistical time unit, and the average total latency of the entire link within each group is calculated. This yields the average latency of the current business type within the preset statistical time unit. Additionally, a line graph showing the average latency of the current business type changing over time is generated with time as the x-axis and the average latency as the y-axis. Finally, a line graph showing the average latency of all business types changing over time is integrated to generate a full-link data statistical chart for the business dimension.

[0012] Preferably, based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption data acquisition link operation status to generate statistical charts showing the percentage of abnormalities in each segment under abnormal link status types, including: According to the preset link status determination rules, the link status of each historical power consumption collection record in the basic analysis wide table is marked. The link status includes link normal status, link unmonitorable status, link interruption status, link loss status, link timeout status, and link uncalculation status. Historical power consumption data collection records marked with link abnormality status are filtered out. For each historical power consumption data collection record marked with link abnormality status, the segment link abnormality information corresponding to the current abnormal historical power consumption data collection record is obtained. The segment link abnormality information includes at least the concentrator data collection link abnormality, internal processing link abnormality, data reporting link abnormality, main station processing link abnormality, and data transmission link abnormality. The number of historical electricity consumption records included in each link abnormal state type is counted to generate a pie chart of the distribution of link abnormal state types. For each segment of abnormal status type, the number of historical electricity consumption data collection records included in the current segment of abnormal status type is counted, and the percentage of the number of such records to the total number of abnormal historical electricity consumption data collection records is calculated to obtain the segment abnormality percentage of the current segment abnormal status type. A pie chart of segment abnormality percentage is then generated based on the segment abnormality percentage of each segment. The pie chart showing the distribution of abnormal link status types is associated with the pie chart showing the percentage of abnormal segments, forming a statistical chart of the percentage of abnormal segments under each abnormal link status type. This allows the user to select any sector in the pie chart showing the distribution of abnormal link status types, and then the pie chart showing the percentage of abnormal segments under the selected abnormal link status type will be displayed in conjunction with this pie chart.

[0013] According to another aspect of this application, a monitoring system for the entire power consumption acquisition chain operation status is provided, comprising: The time tag system construction module is used to expand the electricity information collection protocol based on the target standard specification document and construct the time tag system of the electricity information collection protocol, wherein the time tag system of the electricity information collection protocol contains multiple time tags; The timestamp data acquisition module is used to parse the timestamp data recorded by the acquisition terminal routing application through the acquisition front-end module, extract the timestamp data corresponding to each time tag from the timestamp data, and forward the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset time tag and the message queue topic. The electricity consumption data acquisition end-to-end operation status monitoring module is used to subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link, and based on the timestamp data in the message queue topics that have a mapping relationship with the pre-built real-time processing link, to use the real-time processing link to perform overall real-time monitoring of the operation status of the entire electricity consumption data acquisition link, and generate overall real-time monitoring results. It also subscribes to all the message queue topics, and based on the timestamp data in all the message queue topics, uses the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the operation status of the entire electricity consumption data acquisition link, and generates segmented link data statistical charts.

[0014] Preferably, the timestamp data acquisition module includes: The protocol plugin loading unit is used to load a protocol plugin that supports the electricity information collection protocol time tag system through the acquisition front-end module; The message parsing unit is used to receive the extended protocol message reported by the acquisition terminal routing application based on the protocol plugin, parse the time tags in the extended protocol message to extract the timestamp data corresponding to each time tag, and standardize the full amount of timestamp data to generate multiple standardized intermediate data. A data routing unit is used to push multiple standardized intermediate data to the adapted data routing module, so that the adapted data routing module forwards each standardized intermediate data to the corresponding message queue topic based on the mapping relationship between the preset time tag and the message queue topic.

[0015] Preferably, the message parsing unit is further configured to: For each timestamp data, a preset clock deviation between the acquisition terminal used to collect the current timestamp data and the main station is obtained, and the current timestamp data is corrected based on the preset clock deviation to generate corrected timestamp data, and then the corrected timestamp data is standardized.

[0016] Preferably, the power consumption data acquisition end-to-end operation status monitoring module includes an overall real-time monitoring unit, which is used for: Subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link; Extract the timestamps of the concentrator receiving the main station's collection request, the concentrator's collection start time, and the concentrator's collection completion time from the message queue topics that have a mapping relationship with the real-time processing link; Based on the timestamp of the concentrator receiving the main station's collection request, the timestamp of the concentrator starting collection, and the timestamp of the concentrator completing collection, the total end-to-end time and total end-to-end delay of each real-time power consumption collection record are calculated, and the total end-to-end time and total end-to-end delay are mapped to the real-time power consumption collection record and written into the real-time processing link database. In the real-time processing link database, real-time power consumption collection records with a total total time exceeding a preset threshold and a total delay exceeding a preset threshold are filtered out and output as abnormal alarm information to monitor the overall real-time operation status of the entire power consumption collection link.

[0017] Preferably, the power consumption data acquisition and operation status monitoring module further includes a segmented data analysis unit, which is used for: Subscribe to all the aforementioned message queue topics through the ingestion process; The timestamp data in each of the aforementioned message queue topics are categorized by message queue topic and written into a persistent database for storage; From the persistent database, obtain the full timestamp data of each historical electricity consumption collection record from the previous monitoring period; Based on the full timestamp data, calculate the total end-to-end time, total end-to-end delay, and segmented time data for each of the historical electricity consumption collection records; A basic analysis wide table is generated based on all the historical electricity consumption records and the corresponding total end-to-end time, total end-to-end delay, and segmented link time data. Based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption collection process to generate segmented data statistical charts. These charts include full-link data statistical charts based on business and regional distribution area dimensions, as well as statistical charts showing the percentage of abnormalities in each segment under different abnormal link status types.

[0018] Preferably, the segmented data analysis unit is further used for: For each regional transformer area, the number of historical power consumption collection records in the current regional transformer area whose total end-to-end time exceeds the preset total end-to-end time threshold is counted from the basic analysis wide table. The proportion of the number of historical power consumption collection records that timed out to the total number of historical power consumption collection records in the current regional transformer area is calculated to obtain the abnormality rate of the current regional transformer area. Based on each of the aforementioned anomaly rates, a color level is configured for the corresponding regional transformer area, wherein the color level is proportional to the anomaly rate; For each regional transformer station, locate the geographical area of ​​the current regional transformer station on the electronic map, and render the geographical area according to the color level corresponding to the current regional transformer station to generate a full-link data statistical chart at the regional transformer station dimension; Furthermore, for each business type, multiple historical electricity consumption data collection records included in the current business type are obtained from the basic analysis wide table. These records are then grouped according to a preset statistical time unit, and the average total latency of the entire link within each group is calculated. This yields the average latency of the current business type within the preset statistical time unit. Additionally, a line graph showing the average latency of the current business type changing over time is generated with time as the x-axis and the average latency as the y-axis. Finally, a line graph showing the average latency of all business types changing over time is integrated to generate a full-link data statistical chart for the business dimension.

[0019] Preferably, the segmented data analysis unit is further used for: According to the preset link status determination rules, the link status of each historical power consumption collection record in the basic analysis wide table is marked. The link status includes link normal status, link unmonitorable status, link interruption status, link loss status, link timeout status, and link uncalculation status. Historical power consumption data collection records marked with link abnormality status are filtered out. For each historical power consumption data collection record marked with link abnormality status, the segment link abnormality information corresponding to the current abnormal historical power consumption data collection record is obtained. The segment link abnormality information includes at least the concentrator data collection link abnormality, internal processing link abnormality, data reporting link abnormality, main station processing link abnormality, and data transmission link abnormality. The number of historical electricity consumption records included in each link abnormal state type is counted to generate a pie chart of the distribution of link abnormal state types. For each segment of abnormal status type, the number of historical electricity consumption data collection records included in the current segment of abnormal status type is counted, and the percentage of the number of such records to the total number of abnormal historical electricity consumption data collection records is calculated to obtain the segment abnormality percentage of the current segment abnormal status type. A pie chart of segment abnormality percentage is then generated based on the segment abnormality percentage of each segment. The pie chart showing the distribution of abnormal link status types is associated with the pie chart showing the percentage of abnormal segments, forming a statistical chart of the percentage of abnormal segments under each abnormal link status type. This allows the user to select any sector in the pie chart showing the distribution of abnormal link status types, and then the pie chart showing the percentage of abnormal segments under the selected abnormal link status type will be displayed in conjunction with this pie chart.

[0020] According to another aspect of this application, a storage medium is provided, wherein at least one executable instruction is stored therein, the executable instruction causing a processor to perform an operation corresponding to the above-described monitoring method for the entire power consumption acquisition operation status.

[0021] According to another aspect of this application, a terminal is provided, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other through the communication bus; The memory is used to store at least one executable instruction, which causes the processor to perform the operation corresponding to the above-described monitoring method for the entire power consumption acquisition process.

[0022] By employing the above technical solutions, the technical solutions provided in the embodiments of this application have at least the following advantages: This application provides a method, system, medium, and terminal for monitoring the entire operational status of electricity consumption data collection. First, it expands the electricity consumption information collection protocol based on target standard specifications and constructs a time tag system for the electricity consumption information collection protocol, wherein the time tag system contains multiple time tags. Second, it parses the timestamp data recorded by the routing application of the data collection terminal through a front-end module, extracts the timestamp data corresponding to each time tag from the timestamp data, and, through an adapted data routing module, based on the mapping relationship between preset time tags and message queue topics, processes all the timestamps. Data is forwarded to the corresponding message queue topic; finally, the message queue topics that are mapped to the pre-built real-time processing link are subscribed to, and based on the timestamp data in the message queue topics that are mapped to the pre-built real-time processing link, the real-time processing link is used to perform overall real-time monitoring of the entire power consumption acquisition link operation status, generating overall real-time monitoring results. Additionally, all the message queue topics are subscribed to, and based on the timestamp data in all the message queue topics, the pre-built offline analysis link from the previous monitoring period is used to perform segmented data analysis of the entire power consumption acquisition link operation status, generating segmented data statistical charts. Compared with existing technologies, the embodiments of this application construct a time stamp system for electricity information collection protocols covering the entire electricity collection chain, realizing full-chain timestamp tracking, eliminating observation blind spots between various segments, and enabling refined monitoring of the entire chain's operational status. Simultaneously, by processing the chain in real time, it rapidly outputs overall real-time monitoring results based on specific timestamp data, achieving comprehensive real-time monitoring of the entire electricity collection chain's operational status. Furthermore, by analyzing the chain offline based on all timestamp data from the previous monitoring cycle, it generates segmented segment data statistical charts. This allows for direct location of the specific segment where the anomaly occurred from the segmented segment data statistical charts when collection anomalies or delays occur, eliminating the need for reverse engineering from the business side and significantly improving the efficiency and accuracy of anomaly location.

[0023] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0024] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1A flowchart of a method for monitoring the operational status of the entire power consumption data collection process, according to an embodiment of this application, is shown. Figure 2 A flowchart of another method for monitoring the end-to-end operational status of power consumption data collection provided in an embodiment of this application is shown; Figure 3 This paper shows a block diagram of a monitoring system for the entire power consumption acquisition and operation status according to an embodiment of the present application. Figure 4 A schematic diagram of the structure of a terminal provided in an embodiment of this application is shown. Detailed Implementation

[0025] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0026] This application provides a method for monitoring the operational status of the entire power consumption data acquisition chain, such as... Figure 1 As shown, the method includes: 101. Expand the electricity information collection protocol based on the target standard specification documents, and construct a time tagging system for the electricity information collection protocol.

[0027] The target standard specification document can be the current version of the "Electricity Information Acquisition and Management System" standard specification document. The electricity information acquisition protocol time tag system contains multiple time tags, including but not limited to time tag 9E00 used to characterize the switching of the follow-up reporting time tag function, time tag 6E43 used to characterize the time when the terminal receives the request from the master station, time tag 9E01 used to characterize the details of the electricity meter's collected information, and time tag FE09 used to characterize the carrier or low-power wireless network topology extension information.

[0028] In this embodiment of the application, the current execution terminal can be the master station layer of the electricity information collection system.

[0029] 102. The data acquisition front-end module parses the timestamp data recorded by the acquisition terminal routing application, extracts the timestamp data corresponding to each time tag from the timestamp data, and forwards the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset timestamp and the message queue topic.

[0030] The data acquisition front-end module parses the messages reported by the acquisition terminal routing application and extracts timestamp data. It can perform message parsing based on a protocol plugin that supports the aforementioned electricity information acquisition protocol time stamp system. The acquisition terminal routing application (APP) records timestamp data such as the timestamp when the concentrator receives the master station's acquisition request, the timestamp when the concentrator starts acquisition, and the timestamp when the concentrator completes acquisition. The data routing module distributes the timestamp data extracted by the acquisition front-end module to the corresponding message queue topics. Message queue topics are pre-created Kafka topics based on business requirements. For example, a message queue topic for storing electricity meter acquisition details has a timestamp of 9E01; a message queue topic for storing the time when the terminal receives the master station's request has a timestamp of 6E43; and a message queue topic for storing carrier or low-power wireless network topology extension information has a timestamp of FE09, etc.

[0031] 103. Subscribe to message queue topics that are mapped to pre-built real-time processing links, and based on the timestamp data in the message queue topics that are mapped to pre-built real-time processing links, use the real-time processing links to perform overall real-time monitoring of the entire power consumption acquisition link operation status, generate overall real-time monitoring results, and subscribe to all message queue topics, and based on the timestamp data in all message queue topics, use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the entire power consumption acquisition link operation status, generate segmented link data statistical charts.

[0032] The real-time processing link is used to quickly output overall real-time monitoring results based on specific timestamp data, enabling comprehensive real-time monitoring of the entire power consumption data acquisition chain. The overall real-time monitoring result represents the overall operational status of each real-time power consumption data acquisition record, including normal and abnormal states. This can be determined by comparing the total time consumption and total delay of each real-time power consumption data acquisition record with corresponding preset thresholds. The offline analysis link is used to perform segmented data analysis based on all timestamp data from the previous monitoring period, generating segmented data statistical charts. These charts include full-chain data statistical charts at the business and regional / substation dimensions, as well as abnormal percentage statistical charts for each segment under abnormal link status types. Furthermore, the specific segment where the abnormality occurred can be directly located from these segmented data statistical charts.

[0033] Compared with existing technologies, the embodiments of this application construct a time stamp system for electricity information collection protocols covering the entire electricity collection chain, realizing full-chain timestamp tracking, eliminating observation blind spots between various segments, and enabling refined monitoring of the entire chain's operational status. Simultaneously, by processing the chain in real time, it rapidly outputs overall real-time monitoring results based on specific timestamp data, achieving comprehensive real-time monitoring of the entire electricity collection chain's operational status. Furthermore, by analyzing the chain offline based on all timestamp data from the previous monitoring cycle, it generates segmented segment data statistical charts. This allows for direct location of the specific segment where the anomaly occurred from the segmented segment data statistical charts when collection anomalies or delays occur, eliminating the need for reverse engineering from the business side and significantly improving the efficiency and accuracy of anomaly location.

[0034] This application provides another method for monitoring the entire power consumption data acquisition and operational status, such as... Figure 2 As shown, the method includes: 201. Expand the electricity information collection protocol based on the target standard specification documents, and construct a time tagging system for the electricity information collection protocol.

[0035] Step 201 of the embodiment can be referred to in the detailed description of step 101 of the foregoing embodiment, and will not be repeated here.

[0036] 202. The data acquisition front-end module parses the timestamp data recorded by the acquisition terminal routing application, extracts the timestamp data corresponding to each time tag from the timestamp data, and forwards the full timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset timestamp and the message queue topic.

[0037] Accordingly, step 202 of the embodiment specifically includes: loading a protocol plugin that supports the electricity information collection protocol time tag system through the acquisition front-end module; based on the protocol plugin, receiving the extended protocol message reported by the acquisition terminal routing application, parsing the time tags in the extended protocol message to extract the timestamp data corresponding to each time tag, and standardizing the full timestamp data to generate multiple standardized intermediate data; pushing the multiple standardized intermediate data to the adapted data routing module, so that the adapted data routing module forwards each standardized intermediate data to the corresponding message queue topic based on the mapping relationship between the preset time tag and the message queue topic.

[0038] In this embodiment, firstly, a protocol plugin supporting the electricity information collection protocol time tag system constructed in step 101 of the embodiment is loaded through the acquisition front-end module. The configuration file of this protocol plugin declares each time tag included in the electricity information collection protocol time tag system and its corresponding parsing rules. Further, based on the protocol plugin, extended protocol messages reported by the acquisition terminal routing application are received. These extended protocol messages are obtained by the acquisition terminal routing application by encapsulating the recorded timestamp data according to the acquisition request or active reporting task issued by the main station. They are messages conforming to the expanded electricity information collection protocol and are sent to the acquisition front-end module through a preset channel. Further, the time tags in the extended protocol messages are parsed to extract the timestamp data corresponding to each time tag. Specifically, the time tags in the message are first identified; for example, when OI=9E01 is encountered, it is known that this is a data block of detailed electricity meter collection information. Then, each field value in the detailed electricity meter collection information data block is read one by one according to the predefined structure, and the timestamp data is extracted from it. Furthermore, each timestamp data is converted into key-value pairs or structured data in a unified format to obtain the corresponding standardized intermediate data, which is then pushed to the adapted data routing module. This adapted data routing module can identify and forward the timestamp data corresponding to the timestamp. Finally, through the adapted data routing module, based on the preset mapping relationship between timestamps and message queue topics, each standardized intermediate data is forwarded to the corresponding message queue topic. Optionally, to adapt to high-concurrency scenarios, the data routing module can adopt an asynchronous batch forwarding mechanism. After receiving the standardized intermediate data, it first writes it to a local buffer, and then sends it in batches to the message queue topic after reaching a certain quantity or time threshold, thereby reducing operational overhead. Additionally, when encountering unrecognizable timestamps, they can be recorded and temporarily stored to avoid blocking subsequent data. Furthermore, when data backlog occurs in the message queue topic, flow control can be triggered, and the front-end acquisition module can be notified to reduce the sending rate to prevent further backlog.

[0039] As an optional implementation, before standardizing the full timestamp data and generating multiple standardized intermediate data, the method further includes: for each timestamp data, obtaining the preset clock deviation between the acquisition terminal used to collect the current timestamp data and the main station, and correcting the current timestamp data based on the preset clock deviation to generate corrected timestamp data, so as to standardize the corrected timestamp data.

[0040] Specifically, the correction process is achieved by adding a preset clock offset between the acquisition terminal used to collect the current timestamp data and the master station to the current timestamp data.

[0041] 203. Subscribe to message queue topics that are mapped to the pre-built real-time processing links, and based on the timestamp data in the message queue topics that are mapped to the pre-built real-time processing links, use the real-time processing links to perform overall real-time monitoring of the entire power consumption acquisition link operation status and generate overall real-time monitoring results.

[0042] Accordingly, step 203 of the embodiment specifically includes: subscribing to message queue topics that have a mapping relationship with the pre-built real-time processing link; extracting the timestamps of the concentrator receiving the main station's collection request, the concentrator's collection start time, and the concentrator's collection completion time from the message queue topics that have a mapping relationship with the real-time processing link; calculating the total end-to-end time and total end-to-end delay of each real-time power consumption collection record based on the timestamps of the concentrator receiving the main station's collection request, the concentrator's collection start time, and the concentrator's collection completion time, and mapping the total end-to-end time and total end-to-end delay to the real-time power consumption collection record and writing them into the real-time processing link database; in the real-time processing link database, filtering real-time power consumption collection records whose total end-to-end time exceeds a preset total end-to-end time threshold and whose total end-to-end delay exceeds a preset total end-to-end delay threshold, and outputting them as abnormal alarm information to perform overall real-time monitoring of the entire power consumption collection link operation status.

[0043] In this embodiment, a preset number of consumer instances are first started using the Kafka client library to subscribe to message queue topics that are mapped to the real-time processing link, such as message queue topics storing electricity meter collection details and message queue topics storing the time when the terminal receives the master station request. Further, a multi-threaded concurrent approach can be used to pull messages from the message queue topics mapped to the real-time processing link. From the pulled messages, the timestamps of the concentrator receiving the master station collection request, the concentrator collection start time, and the concentrator collection completion time for each real-time electricity consumption collection record are extracted. Further, based on these timestamps, the total end-to-end time and total end-to-end delay for each real-time electricity consumption collection record are calculated. These timestamps are then mapped to the real-time electricity consumption collection record and written into the real-time processing link database. Specifically, the total end-to-end time = timestamp of the concentrator receiving the master station collection request - timestamp of the concentrator collection start time; the total end-to-end delay = timestamp of the concentrator collection completion - timestamp of the concentrator receiving the master station collection request. Finally, in the real-time processing link database, real-time power consumption collection records with a total total time exceeding a preset threshold and a total delay exceeding a preset threshold are filtered out. These are identified as real-time power consumption collection records in an abnormal state and output as abnormal alarm information to perform overall real-time monitoring of the entire power consumption collection link operation status.

[0044] 204. Subscribe to all message queue topics, and based on the timestamp data in all message queue topics, use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis on the operation status of the entire power consumption collection link, and generate segmented link data statistical charts.

[0045] Accordingly, step 204 of the embodiment specifically includes: subscribing to all message queue topics through the database entry program; writing the timestamp data in each message queue topic into a persistent database for storage according to the message queue topic classification; obtaining the full timestamp data of each historical electricity consumption collection record in the previous monitoring period from the persistent database; calculating the total end-to-end time, total end-to-end delay, and segmented stage time data for each historical electricity consumption collection record based on the full timestamp data; generating a basic analysis wide table based on all historical electricity consumption collection records and the corresponding total end-to-end time, total end-to-end delay, and segmented stage time data; and performing segmented stage data analysis on the end-to-end operation status of electricity consumption collection based on the basic analysis wide table, and generating segmented stage data statistical charts.

[0046] In this embodiment, multiple consumer instances can be started using the Kafka client library to subscribe to all message queue topics, and the timestamp data in each message queue topic can be written to a persistent database for storage according to the message queue topic. When performing segmented data analysis, the full timestamp data of each historical electricity consumption collection record from the previous monitoring period is obtained from the persistent database, and data preprocessing is performed. This preprocessing may include removing timestamp data with incorrect formatting, removing timestamp data with logical errors, and removing duplicate historical electricity consumption collection records. The monitoring period can be set to 1 day, 1 week, etc., and is not specifically limited in this embodiment. Further, based on the full timestamp data, the total end-to-end time, total end-to-end latency, and segmented time data for each historical electricity consumption collection record are calculated. The segmented time data includes at least the concentrator collection time, concentrator internal processing time, concentrator data reporting time, main station processing time, and data transmission time. Finally, the historical electricity consumption data is mapped to the corresponding total end-to-end time, total end-to-end delay, and segmented time data, and used as a row of data in the basic analysis wide table. All rows of data are then integrated to generate the basic analysis wide table.

[0047] It should be noted that the segmented data statistics charts include full-link data statistics charts at the business dimension and regional station dimension, as well as statistics charts on the abnormal percentage of each segment under abnormal link status types.

[0048] Specifically, based on the basic analysis wide table, segmented data analysis is performed on the entire power consumption data collection process to generate statistical charts of the entire data collection process at both the business and regional transformer area levels. This includes: for each regional transformer area, counting the number of historical power consumption data collection records in the current regional transformer area whose total timeout exceeds a preset threshold, and calculating the percentage of these expired records relative to the total number of historical records in the current regional transformer area to obtain the anomaly rate; configuring color levels for the corresponding regional transformer areas based on each anomaly rate, where the color level is proportional to the anomaly rate; and locating the geographical area of ​​each regional transformer area on the electronic map and mapping the geographical area... The region is rendered with the color level corresponding to the current region's transformer area to generate a full-link data statistical chart at the region's transformer area level. Furthermore, for each service type, multiple historical electricity consumption records are retrieved from the basic analysis wide table. These records are then grouped according to a preset statistical time unit, and the average total latency of the historical electricity consumption records within each group is calculated. This yields the average latency of the current service type within the preset statistical time unit. Additionally, a line graph showing the average latency of the current service type changing over time is generated, with time as the x-axis and the average latency as the y-axis. Finally, a line graph integrating the average latency of all service types changing over time is used to generate a full-link data statistical chart at the service dimension.

[0049] For example, when configuring color levels, the color level can be configured as green when the anomaly rate is 0 ≤ anomaly rate ≤ 2%, as yellow when the anomaly rate is 2% < anomaly rate ≤ 5%, as orange when the anomaly rate is 5% < anomaly rate ≤ 10%, and as red when the anomaly rate is > 10%. That is, the higher the anomaly rate, the darker or brighter the color level, serving as a warning. Service types include, but are not limited to, 15-minute freezes and load management. The preset statistical time unit can be daily or monthly; this embodiment does not impose a specific limitation.

[0050] Based on the basic analysis wide table, segmented data analysis is performed on the entire power consumption data acquisition link operation status. This generates statistical charts showing the percentage of abnormalities in each segment under different abnormal link status types. This includes: marking the link status of each historical power consumption data acquisition record in the basic analysis wide table according to preset link status judgment rules. Link status includes normal link status, unmonitorable link status, interrupted link status, lost link status, timeout link status, and uncalculable link status; filtering historical power consumption data acquisition records marked with abnormal link status; and for each historical power consumption data acquisition record marked with abnormal link status, obtaining the corresponding segment abnormality information for the current abnormal historical power consumption data acquisition record. This segment abnormality information includes at least concentrator acquisition abnormality, internal processing abnormality, data reporting abnormality, main station processing abnormality, and data transmission abnormality. The following steps are performed: First, count the number of historical electricity consumption records included in each link anomaly status type to generate a pie chart showing the distribution of link anomaly status types. Then, for each segment anomaly status type, count the number of historical electricity consumption records included in the current segment anomaly status type and calculate the percentage of these records relative to the total number of abnormal historical electricity consumption records. This yields the segment anomaly percentage for the current segment anomaly status type, and a pie chart showing the segment anomaly percentage is generated based on this percentage. Finally, associate the link anomaly status type distribution pie chart with the segment anomaly percentage pie chart to create a statistical chart showing the anomaly percentage of each segment under each link anomaly status type. This ensures that when a user selects any sector in the link anomaly status type distribution pie chart, the pie chart showing the anomaly percentage of each segment under the selected link anomaly status type is displayed.

[0051] In this embodiment, the link status of each historical electricity consumption data collection record in the basic analysis wide table is first marked according to preset link status determination rules. For example, historical electricity consumption data collection records lacking necessary timestamp data are classified as unmonitorable links; historical electricity consumption data collection records with multiple consecutive unresponsive events are classified as interrupted links; historical electricity consumption data collection records with registration failures or routing failures are classified as lost links; historical electricity consumption data collection records with collection time exceeding a threshold are classified as timeout links; historical electricity consumption data collection records with logical errors in timestamps are classified as uncalculable links; and historical electricity consumption data collection records without the above defects are classified as normal links. Further, the number of historical electricity consumption data collection records included in each link abnormality status type is counted to generate a pie chart of link abnormality status type distribution. Further, for each historical electricity consumption data collection record marked with a link abnormality status, the corresponding segment link abnormality information is obtained to determine its specific segment link abnormality status type. Furthermore, for each segment's abnormal status type, the number of historical electricity consumption records included in it is counted, and the percentage of this number to the total number of abnormal historical electricity consumption records is calculated. This percentage is used as the segment's abnormal status percentage for the current segment, and a pie chart of segment abnormal status percentages is generated based on each segment's abnormal status percentage. Finally, a synchronized display is implemented.

[0052] As an optional implementation, abnormal historical electricity consumption records can be associated with the corresponding meter addresses and regional transformer area identifiers, and regional transformer area topology data can be maintained in advance. A positioning button can also be set in the basic analysis wide table so that when the positioning button is clicked, the corresponding meter node can be automatically located.

[0053] As an optional implementation, the number of terminals from each manufacturer that have anomalies in the data collection, internal processing, and data reporting stages can be counted, and the manufacturer's anomaly rate can be calculated. The manufacturer's anomaly rate = number of terminals from that manufacturer with anomalies in at least one stage / total number of terminals from that manufacturer × 100%. Ranking information is generated based on the anomaly rate and displayed in a carousel to urge manufacturers to reduce their anomaly rates.

[0054] As an optional implementation, automatic diagnosis can also be performed in the following five-level sequence for scenarios where data collection fails on T-1 day or the terminal goes offline: Level 1: Determine if there is a T-1 day freeze data collection failure. If not, output a non-data collection failure error message. If yes, proceed to Level 2. The second level determines whether the terminal is offline. If not, it jumps to the fourth level; if it is, it proceeds to the third level. The third level determines whether the system file parameters are consistent with the on-site parameters. If not, it outputs handling suggestions for inconsistent file parameters and ends the diagnosis. If yes, it proceeds to the fourth level. Level 4: Perform uplink channel anomaly analysis. If an uplink anomaly is determined, output uplink channel anomaly handling suggestions and end the diagnosis; otherwise, proceed to Level 5. Level 5: Perform downlink channel anomaly analysis and output handling suggestions for downlink channel anomalies or meter malfunctions.

[0055] This application provides a method for monitoring the operational status of the entire electricity consumption data acquisition chain. First, the electricity consumption information acquisition protocol is expanded based on the target standard specification document, and a time tag system for the electricity consumption information acquisition protocol is constructed, wherein the time tag system contains multiple time tags. Second, the timestamp data recorded by the acquisition terminal routing application is parsed by the acquisition front-end module, and the timestamp data corresponding to each time tag is extracted from the timestamp data. Then, through an adapted data routing module, based on the mapping relationship between preset time tags and message queue topics, all the timestamp data is forwarded to the corresponding message queue topics. Finally, message queue topics that have a mapping relationship with the pre-built real-time processing link are subscribed to, and based on the timestamp data in the message queue topics that have a mapping relationship with the pre-built real-time processing link, the real-time processing link is used to perform overall real-time monitoring of the operational status of the entire electricity consumption data acquisition chain, generating an overall real-time monitoring result. Additionally, all message queue topics are subscribed to, and based on the timestamp data in all message queue topics, the pre-built offline analysis link of the previous monitoring cycle is used to perform segmented data analysis of the operational status of the entire electricity consumption data acquisition chain, generating segmented segmented data statistical charts. Compared with existing technologies, the embodiments of this application construct a time stamp system for electricity information collection protocols covering the entire electricity collection chain, realizing full-chain timestamp tracking, eliminating observation blind spots between various segments, and enabling refined monitoring of the entire chain's operational status. Simultaneously, by processing the chain in real time, it rapidly outputs overall real-time monitoring results based on specific timestamp data, achieving comprehensive real-time monitoring of the entire electricity collection chain's operational status. Furthermore, by analyzing the chain offline based on all timestamp data from the previous monitoring cycle, it generates segmented segment data statistical charts. This allows for direct location of the specific segment where the anomaly occurred from the segmented segment data statistical charts when collection anomalies or delays occur, eliminating the need for reverse engineering from the business side and significantly improving the efficiency and accuracy of anomaly location.

[0056] Furthermore, as a response to the above Figure 1 The implementation of the method shown in this application provides a monitoring system for the entire power consumption data acquisition chain, such as... Figure 3 As shown, the system includes: Module 31 for constructing a time tag system; Module 32 for collecting timestamp data; Module 33 for monitoring the full-link operation status of electricity consumption data collection. The time tag system construction module 31 is used to expand the electricity information collection protocol based on the target standard specification document and construct the time tag system of the electricity information collection protocol, wherein the time tag system of the electricity information collection protocol contains multiple time tags; The timestamp data acquisition module 32 is used to parse the timestamp data recorded by the acquisition terminal routing application through the acquisition front-end module, extract the timestamp data corresponding to each time tag from the timestamp data, and forward the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset time tag and the message queue topic. The power consumption acquisition end-to-end operation status monitoring module 33 is used to subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link, and based on the timestamp data in the message queue topics that have a mapping relationship with the pre-built real-time processing link, to use the real-time processing link to perform overall real-time monitoring of the power consumption acquisition end-to-end operation status, generate overall real-time monitoring results, and subscribe to all the message queue topics, and based on the timestamp data in all the message queue topics, to use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the power consumption acquisition end-to-end operation status, generate segmented link data statistical charts.

[0057] In specific application scenarios, the timestamp data acquisition module includes: The protocol plugin loading unit is used to load a protocol plugin that supports the electricity information collection protocol time tag system through the acquisition front-end module; The message parsing unit is used to receive the extended protocol message reported by the acquisition terminal routing application based on the protocol plugin, parse the time tags in the extended protocol message to extract the timestamp data corresponding to each time tag, and standardize the full amount of timestamp data to generate multiple standardized intermediate data. A data routing unit is used to push multiple standardized intermediate data to the adapted data routing module, so that the adapted data routing module forwards each standardized intermediate data to the corresponding message queue topic based on the mapping relationship between the preset time tag and the message queue topic.

[0058] In specific application scenarios, the message parsing unit is also used for: For each timestamp data, a preset clock deviation between the acquisition terminal used to collect the current timestamp data and the main station is obtained, and the current timestamp data is corrected based on the preset clock deviation to generate corrected timestamp data, and then the corrected timestamp data is standardized.

[0059] In specific application scenarios, the power consumption data acquisition end-to-end operation status monitoring module includes an overall real-time monitoring unit, which is used for: Subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link; Extract the timestamps of the concentrator receiving the main station's collection request, the concentrator's collection start time, and the concentrator's collection completion time from the message queue topics that have a mapping relationship with the real-time processing link; Based on the timestamp of the concentrator receiving the main station's collection request, the timestamp of the concentrator starting collection, and the timestamp of the concentrator completing collection, the total end-to-end time and total end-to-end delay of each real-time power consumption collection record are calculated, and the total end-to-end time and total end-to-end delay are mapped to the real-time power consumption collection record and written into the real-time processing link database. In the real-time processing link database, real-time power consumption collection records with a total total time exceeding a preset threshold and a total delay exceeding a preset threshold are filtered out and output as abnormal alarm information to monitor the overall real-time operation status of the entire power consumption collection link.

[0060] In specific application scenarios, the power consumption data acquisition and operation status monitoring module further includes a segmented data analysis unit, which is used for: Subscribe to all the aforementioned message queue topics through the ingestion process; The timestamp data in each of the aforementioned message queue topics are categorized by message queue topic and written into a persistent database for storage; From the persistent database, obtain the full timestamp data of each historical electricity consumption collection record from the previous monitoring period; Based on the full timestamp data, calculate the total end-to-end time, total end-to-end delay, and segmented time data for each of the historical electricity consumption collection records; A basic analysis wide table is generated based on all the historical electricity consumption records and the corresponding total end-to-end time, total end-to-end delay, and segmented link time data. Based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption collection process to generate segmented data statistical charts. These charts include full-link data statistical charts based on business and regional distribution area dimensions, as well as statistical charts showing the percentage of abnormalities in each segment under different abnormal link status types.

[0061] In specific application scenarios, the segmented data analysis unit is also used for: For each regional transformer area, the number of historical power consumption collection records in the current regional transformer area whose total end-to-end time exceeds the preset total end-to-end time threshold is counted from the basic analysis wide table. The proportion of the number of historical power consumption collection records that timed out to the total number of historical power consumption collection records in the current regional transformer area is calculated to obtain the abnormality rate of the current regional transformer area. Based on each of the aforementioned anomaly rates, a color level is configured for the corresponding regional transformer area, wherein the color level is proportional to the anomaly rate; For each regional transformer station, locate the geographical area of ​​the current regional transformer station on the electronic map, and render the geographical area according to the color level corresponding to the current regional transformer station to generate a full-link data statistical chart at the regional transformer station dimension; Furthermore, for each business type, multiple historical electricity consumption data collection records included in the current business type are obtained from the basic analysis wide table. These records are then grouped according to a preset statistical time unit, and the average total latency of the entire link within each group is calculated. This yields the average latency of the current business type within the preset statistical time unit. Additionally, a line graph showing the average latency of the current business type changing over time is generated with time as the x-axis and the average latency as the y-axis. Finally, a line graph showing the average latency of all business types changing over time is integrated to generate a full-link data statistical chart for the business dimension.

[0062] In specific application scenarios, the segmented data analysis unit is also used for: According to the preset link status determination rules, the link status of each historical power consumption collection record in the basic analysis wide table is marked. The link status includes link normal status, link unmonitorable status, link interruption status, link loss status, link timeout status, and link uncalculation status. Historical power consumption data collection records marked with link abnormality status are filtered out. For each historical power consumption data collection record marked with link abnormality status, the segment link abnormality information corresponding to the current abnormal historical power consumption data collection record is obtained. The segment link abnormality information includes at least the concentrator data collection link abnormality, internal processing link abnormality, data reporting link abnormality, main station processing link abnormality, and data transmission link abnormality. The number of historical electricity consumption records included in each link abnormal state type is counted to generate a pie chart of the distribution of link abnormal state types. For each segment of abnormal status type, the number of historical electricity consumption data collection records included in the current segment of abnormal status type is counted, and the proportion of the number to the total number of abnormal historical electricity consumption data collection records is calculated to obtain the segment abnormality proportion of the current segment abnormal status type. A pie chart of segment abnormality proportion is generated based on the segment abnormality proportion of each segment. The pie chart showing the distribution of abnormal link status types is associated with the pie chart showing the percentage of abnormal segments, forming a statistical chart of the percentage of abnormal segments under each abnormal link status type. This allows the user to select any sector in the pie chart showing the distribution of abnormal link status types, and then simultaneously display the pie chart showing the percentage of abnormal segments under the selected abnormal link status type.

[0063] This application provides a monitoring system for the entire power consumption data acquisition chain operation status. First, it expands the power consumption information acquisition protocol based on target standard specifications and constructs a time tag system for the power consumption information acquisition protocol, which includes multiple time tags. Second, it parses the timestamp data recorded by the acquisition terminal routing application through a front-end module, extracts the timestamp data corresponding to each time tag from the timestamp data, and forwards all the timestamp data to the corresponding message queue topic based on the mapping relationship between preset timestamps and message queue topics through an adapted data routing module. Finally, it subscribes to message queue topics that have a mapping relationship with a pre-built real-time processing link, and uses the timestamp data in the message queue topics to perform overall real-time monitoring of the entire power consumption data acquisition chain operation status, generating an overall real-time monitoring result. It also subscribes to all the message queue topics, and uses the pre-built offline analysis link from the previous monitoring cycle to perform segmented data analysis of the entire power consumption data acquisition chain operation status, generating segmented data statistical charts based on the timestamp data in all message queue topics. Compared with existing technologies, the embodiments of this application construct a time stamp system for electricity information collection protocols covering the entire electricity collection chain, realizing full-chain timestamp tracking, eliminating observation blind spots between various segments, and enabling refined monitoring of the entire chain's operational status. Simultaneously, by processing the chain in real time, it rapidly outputs overall real-time monitoring results based on specific timestamp data, achieving comprehensive real-time monitoring of the entire electricity collection chain's operational status. Furthermore, by analyzing the chain offline based on all timestamp data from the previous monitoring cycle, it generates segmented segment data statistical charts. This allows for direct location of the specific segment where the anomaly occurred from the segmented segment data statistical charts when collection anomalies or delays occur, eliminating the need for reverse engineering from the business side and significantly improving the efficiency and accuracy of anomaly location.

[0064] According to one embodiment of this application, a storage medium is provided, the storage medium storing at least one executable instruction, which can execute the monitoring method for the entire power consumption acquisition operation status in any of the above method embodiments.

[0065] Based on this understanding, the technical solution of this application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, or portable hard drive), and includes several instructions to cause a computer device (such as a personal computer, server, or network device) to execute the methods described in the various implementation scenarios of this application.

[0066] Figure 4The diagram shows a structural schematic of a terminal according to one embodiment of the present application. The specific embodiments of the present application do not limit the specific implementation of the terminal.

[0067] like Figure 4 As shown, the terminal may include: a processor 402, a communication interface 404, a memory 406, and a communication bus 408.

[0068] The processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408.

[0069] Communication interface 404 is used to communicate with other network elements such as clients or other servers.

[0070] The processor 402 is used to execute program 410, specifically to execute the relevant steps in the above-described embodiment of the monitoring method for the entire power consumption acquisition operation status.

[0071] Specifically, program 410 may include program code that includes computer operation instructions.

[0072] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application. The computer device includes one or more processors, which may be processors of the same type, such as one or more CPUs; or they may be processors of different types, such as one or more CPUs and one or more ASICs.

[0073] Memory 406 is used to store program 410. Memory 406 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0074] Specifically, program 410 can be used to cause processor 402 to perform the following operations: The electricity consumption information collection protocol is expanded based on the target standard specification documents, and a time tag system for the electricity consumption information collection protocol is constructed, wherein the time tag system for the electricity consumption information collection protocol contains multiple time tags; The data acquisition front-end module parses the timestamp data recorded by the acquisition terminal routing application, extracts the timestamp data corresponding to each time tag from the timestamp data, and forwards the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset timestamp and the message queue topic. Subscribe to message queue topics that are mapped to pre-built real-time processing links, and based on the timestamp data in the message queue topics that are mapped to the pre-built real-time processing links, use the real-time processing links to perform overall real-time monitoring of the entire power consumption acquisition link operation status, and generate overall real-time monitoring results. Also, subscribe to all the message queue topics, and based on the timestamp data in all the message queue topics, use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the entire power consumption acquisition link operation status, and generate segmented link data statistical charts.

[0075] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the physical device for the aforementioned monitoring method of the entire power consumption acquisition chain, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0076] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0077] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for monitoring the operational status of the entire power consumption data chain, characterized in that, include: The electricity consumption information collection protocol is expanded based on the target standard specification documents, and a time tag system for the electricity consumption information collection protocol is constructed, wherein the time tag system for the electricity consumption information collection protocol contains multiple time tags; The data acquisition front-end module parses the timestamp data recorded by the acquisition terminal routing application, extracts the timestamp data corresponding to each time tag from the timestamp data, and forwards the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset timestamp and the message queue topic. Subscribe to message queue topics that are mapped to pre-built real-time processing links, and based on the timestamp data in the message queue topics that are mapped to pre-built real-time processing links, use the real-time processing links to perform overall real-time monitoring of the entire power consumption acquisition link operation status, generate overall real-time monitoring results, and subscribe to all the message queue topics, and based on the timestamp data in all the message queue topics, use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the entire power consumption acquisition link operation status, generate segmented link data statistical charts; Specifically, the subscription to all message queue topics, and based on the timestamp data in all message queue topics, the segmented data analysis of the entire power consumption data collection process using the pre-built offline analysis link from the previous monitoring period, generates segmented data statistical charts, including: Subscribe to all the aforementioned message queue topics through the ingestion process; The timestamp data in each of the aforementioned message queue topics are categorized by message queue topic and written into a persistent database for storage; From the persistent database, obtain the full timestamp data of each historical electricity consumption collection record from the previous monitoring period; Based on the full timestamp data, calculate the total end-to-end time, total end-to-end delay, and segmented time data for each of the historical electricity consumption collection records; A basic analysis wide table is generated based on all the historical electricity consumption records and the corresponding total end-to-end time, total end-to-end delay, and segmented link time data. Based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption collection process to generate segmented data statistical charts. These charts include full-link data statistical charts based on business and regional distribution area dimensions, as well as statistical charts showing the percentage of abnormalities in each segment under different abnormal link status types.

2. The method according to claim 1, characterized in that, The process involves parsing the timestamp data recorded by the acquisition terminal routing application through the acquisition front-end module, extracting the timestamp data corresponding to each time tag from the timestamp data, and forwarding the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the preset mapping relationship between time tags and message queue topics. This includes: The acquisition front-end module loads a protocol plugin that supports the electricity consumption information acquisition protocol time tag system; Based on the protocol plugin, the extended protocol message reported by the routing application of the acquisition terminal is received, the time tags in the extended protocol message are parsed and processed to extract the timestamp data corresponding to each time tag, and the full set of timestamp data is standardized to generate multiple standardized intermediate data. Multiple standardized intermediate data are pushed to the adapted data routing module, so that the adapted data routing module forwards each standardized intermediate data to the corresponding message queue topic based on the mapping relationship between the preset time tag and the message queue topic.

3. The method according to claim 2, characterized in that, Before standardizing the entire set of timestamp data to generate multiple standardized intermediate data, the method further includes: For each timestamp data, a preset clock deviation between the acquisition terminal used to collect the current timestamp data and the main station is obtained, and the current timestamp data is corrected based on the preset clock deviation to generate corrected timestamp data, and then the corrected timestamp data is standardized.

4. The method according to claim 1, characterized in that, The message queue topics that are mapped to the pre-built real-time processing links are used to perform overall real-time monitoring of the entire power consumption data collection process based on the timestamp data in the message queue topics mapped to the pre-built real-time processing links, generating overall real-time monitoring results, including: Subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link; Extract the timestamps of the concentrator receiving the main station's collection request, the concentrator's collection start time, and the concentrator's collection completion time from the message queue topics that have a mapping relationship with the real-time processing link; Based on the timestamp of the concentrator receiving the main station's collection request, the timestamp of the concentrator starting collection, and the timestamp of the concentrator completing collection, the total end-to-end time and total end-to-end delay of each real-time power consumption collection record are calculated, and the total end-to-end time and total end-to-end delay are mapped to the real-time power consumption collection record and written into the real-time processing link database. In the real-time processing link database, real-time power consumption collection records with a total total time exceeding a preset threshold and a total delay exceeding a preset threshold are filtered out and output as abnormal alarm information to monitor the overall real-time operation status of the entire power consumption collection link.

5. The method according to claim 1, characterized in that, Based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption data acquisition process to generate full-link data statistical charts at both the business and regional transformer area levels, including: For each regional transformer area, the number of historical power consumption collection records in the current regional transformer area whose total end-to-end time exceeds the preset total end-to-end time threshold is counted from the basic analysis wide table. The proportion of the number of historical power consumption collection records that timed out to the total number of historical power consumption collection records in the current regional transformer area is calculated to obtain the abnormality rate of the current regional transformer area. Based on each of the aforementioned anomaly rates, a color level is configured for the corresponding regional transformer area, wherein the color level is proportional to the anomaly rate; For each regional transformer station, locate the geographical area of ​​the current regional transformer station on the electronic map, and render the geographical area according to the color level corresponding to the current regional transformer station to generate a full-link data statistical chart at the regional transformer station dimension; Furthermore, for each business type, multiple historical electricity consumption data collection records included in the current business type are obtained from the basic analysis wide table. These records are then grouped according to a preset statistical time unit, and the average total latency of the entire link within each group is calculated. This yields the average latency of the current business type within the preset statistical time unit. Additionally, a line graph showing the average latency of the current business type changing over time is generated with time as the x-axis and the average latency as the y-axis. Finally, a line graph showing the average latency of all business types changing over time is integrated to generate a full-link data statistical chart for the business dimension.

6. The method according to claim 1, characterized in that, Based on the aforementioned basic analysis wide table, segmented data analysis is performed on the entire power consumption data acquisition chain operation status, generating statistical charts of the abnormal percentage of each segment under abnormal link status types, including: According to the preset link status determination rules, the link status of each historical power consumption collection record in the basic analysis wide table is marked. The link status includes link normal status, link unmonitorable status, link interruption status, link loss status, link timeout status, and link uncalculation status. Historical power consumption data collection records marked with link abnormality status are filtered out. For each historical power consumption data collection record marked with link abnormality status, the segment link abnormality information corresponding to the current abnormal historical power consumption data collection record is obtained. The segment link abnormality information includes at least the concentrator data collection link abnormality, internal processing link abnormality, data reporting link abnormality, main station processing link abnormality, and data transmission link abnormality. The number of historical electricity consumption records included in each link abnormal state type is counted to generate a pie chart of the distribution of link abnormal state types. For each segment of abnormal status type, the number of historical electricity consumption data collection records included in the current segment of abnormal status type is counted, and the percentage of the number of such records to the total number of abnormal historical electricity consumption data collection records is calculated to obtain the segment abnormality percentage of the current segment abnormal status type. A pie chart of segment abnormality percentage is then generated based on the segment abnormality percentage of each segment. The pie chart showing the distribution of abnormal link status types is associated with the pie chart showing the percentage of abnormal segments, forming a statistical chart of the percentage of abnormal segments under each abnormal link status type. This allows the user to select any sector in the pie chart showing the distribution of abnormal link status types, and then the pie chart showing the percentage of abnormal segments under the selected abnormal link status type will be displayed in conjunction with this pie chart.

7. A monitoring system for collecting the operational status of the entire power supply chain, characterized in that, include: The time tag system construction module is used to expand the electricity information collection protocol based on the target standard specification document and construct the time tag system of the electricity information collection protocol, wherein the time tag system of the electricity information collection protocol contains multiple time tags; The timestamp data acquisition module is used to parse the timestamp data recorded by the acquisition terminal routing application through the acquisition front-end module, extract the timestamp data corresponding to each time tag from the timestamp data, and forward the full amount of timestamp data to the corresponding message queue topic through the adapted data routing module based on the mapping relationship between the preset time tag and the message queue topic. The power consumption data acquisition end-to-end operation status monitoring module is used to subscribe to message queue topics that have a mapping relationship with the pre-built real-time processing link, and based on the timestamp data in the message queue topics that have a mapping relationship with the pre-built real-time processing link, to use the real-time processing link to perform overall real-time monitoring of the power consumption data acquisition end-to-end operation status, generate overall real-time monitoring results, and subscribe to all the message queue topics, and based on the timestamp data in all the message queue topics, to use the pre-built offline analysis link of the previous monitoring period to perform segmented link data analysis of the power consumption data acquisition end-to-end operation status, generate segmented link data statistical charts; The electricity consumption data acquisition end-to-end operation status monitoring module is specifically used to subscribe to all the message queue topics through the database entry program; write the timestamp data of each message queue topic into a persistent database for storage according to the message queue topic classification; obtain the full timestamp data of each historical electricity consumption data acquisition record of the previous monitoring period from the persistent database; calculate the total end-to-end time, total end-to-end delay, and segmented link time data for each historical electricity consumption data acquisition record based on the full timestamp data; generate a basic analysis wide table based on all the historical electricity consumption data acquisition records and the corresponding total end-to-end time, total end-to-end delay, and segmented link time data; and perform segmented link data analysis on the end-to-end operation status of electricity consumption data acquisition based on the basic analysis wide table, generating segmented link data statistical charts, wherein the segmented link data statistical charts include end-to-end data statistical charts of business dimension and regional transformer area dimension, as well as abnormal percentage statistical charts of each segmented link under abnormal link status type.

8. A storage medium storing at least one executable instruction, characterized in that, The executable instructions cause the processor to perform the operations corresponding to the monitoring method for the entire power consumption acquisition operation status as described in any one of claims 1-6.

9. A terminal, comprising: The processor, memory, communication interface, and communication bus are provided, wherein the processor, memory, and communication interface communicate with each other via the communication bus. The memory is used to store at least one executable instruction, characterized in that the executable instruction causes the processor to perform the operation corresponding to the monitoring method for the full-link operation status of power consumption acquisition as described in any one of claims 1-6.

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