Data processing system, method and device

Abstract

The embodiment of the invention provides a data processing system, method and device. The data processing system comprises at least two first clients and a second client, the target client is configured to determine a data acquisition index according to point table data of a power station, acquire target data corresponding to the data acquisition index at the power station by operating a data acquisition program, and transmit the target data and a power station identifier of the power station to a data warehouse for storage through a network tunnel; wherein the target client is each of the at least two first clients; and the second client is configured to acquire target data corresponding to at least two power stations in the data warehouse according to the power station identifiers of the at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display an analysis result according to a preset display form.

Description

Technical Field

[0001] The embodiments of the present specification relate to the field of computer technology, and in particular, to a data processing system. Background Art

[0002] At present, for the multiple power stations that have been put into use, due to the different geographical locations of the deployment of each power station and the distance between the power stations is often far apart, in order to facilitate the observation of various data in the power station, each power station is equipped with a set of master control screens that comprehensively display the basic information of the facilities and operation data in the station. However, if you need to conveniently view the detailed data of all power stations, the operation and maintenance personnel need to integrate the data of all power stations for comprehensive analysis and processing. The existing model is to extract key data one by one from the independent databases of each power station, and then summarize, analyze and visualize them. This process not only consumes a lot of manpower and material resources, but also makes it difficult to achieve the expected ideal effect and efficiency. Therefore, an optimization solution is urgently needed to solve such problems. Summary of the invention

[0003] In view of this, an embodiment of this specification provides a data processing system. One or more embodiments of this specification also relate to a data processing method, a data processing device, a computing device, a computer-readable storage medium and a computer program to solve the technical defects existing in the prior art.

[0004] According to a first aspect of an embodiment of this specification, there is provided a data processing system, including: at least two first clients and a second client;

[0005] A target client is configured to determine a data collection index according to the point meter data of the power station, and to collect target data corresponding to the data collection index at the power station by running a data collection program, and to transmit the target data and the power station identifier of the power station to a data warehouse through a network tunnel for storage; wherein the target client is each of the at least two first clients;

[0006] The second client is configured to obtain the target data corresponding to the at least two power stations in the data warehouse according to the power station identifiers of the at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format.

[0007] Optionally, the target client is also configured to: collect target data corresponding to the data collection index within a preset time period in the power station by running a data collection program, and compare the number of collected target data with a preset number, and determine the communication status between the target client and the power station according to the comparison result.

[0008] Optionally, the target client is also configured to: determine data collection indicators based on at least two fields contained in the information point table of the power station, and obtain target data corresponding to the data collection indicators within a preset time period at the power station by running a data collection program, and write the target data and the power station identifier of the power station into a temporary file.

[0009] Optionally, the target client is also configured to: call the analysis function to read the target data corresponding to the power station identifier in the temporary file, determine the number of target data items by traversing the target data, and compare the number of target data items with a preset number, and when it is determined according to the comparison result that the number of target data items is less than the preset number, determine that the communication status between the target client and the power station is abnormal; or, when it is determined according to the comparison result that the number of target data items is equal to the preset number, determine that the communication status between the target client and the power station is normal, and transmit the target data and the power station identifier of the power station to the data warehouse through a network tunnel for storage.

[0010] Optionally, the second client is also configured to: obtain, according to the power station identifications of at least two power stations, first target data of the first time interval and second target data of the second time interval corresponding to the at least two power stations in the data warehouse, respectively, perform statistical analysis on the first target data and the second target data, generate first analysis results and second analysis results, and display the first analysis results in a first display format, and display the second analysis results in a second display format.

[0011] Optionally, the first time interval includes a current time interval, and the second time interval includes a historical time interval; the first display form includes a pie chart form, and the second display form includes a curve chart form.

[0012] According to a second aspect of an embodiment of this specification, a data processing method is provided, including:

[0013] Determine a data collection index according to the point meter data of the power station, and collect target data corresponding to the data collection index at the power station by running a data collection program;

[0014] Transmitting the target data and the power station identifier of the power station to a data warehouse for storage through a network tunnel;

[0015] Acquire target data corresponding to the at least two power stations respectively in the data warehouse according to the power station identifiers of the at least two power stations;

[0016] Statistical analysis is performed on the target data corresponding to the at least two power stations, and the analysis results are displayed in a preset display format.

[0017] According to a third aspect of an embodiment of this specification, there is provided a data processing device, including:

[0018] A collection module is configured to determine a data collection index according to the point meter data of the power station, and collect target data corresponding to the data collection index in the power station by running a data collection program;

[0019] a transmission module, configured to transmit the target data and the power station identification of the power station to a data warehouse for storage through a network tunnel;

[0020] an acquisition module, configured to acquire target data respectively corresponding to the at least two power stations in the data warehouse according to power station identifiers of the at least two power stations;

[0021] The display module is configured to perform statistical analysis on the target data corresponding to the at least two power stations respectively, and display the analysis results in a preset display format.

[0022] According to a fourth aspect of an embodiment of this specification, a computing device is provided, including:

[0023] Memory and processor;

[0024] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement any step of the data processing method.

[0025] According to a fifth aspect of the embodiments of this specification, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of any one of the data processing methods are implemented.

[0026] According to a sixth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned data processing method.

[0027] In one embodiment of the present specification, the target client first determines the data collection index according to the point table data of the power station, and collects the target data corresponding to the data collection index at the power station by running the data collection program, and transmits the target data and the power station identification of the power station to the data warehouse for storage through the network tunnel; the second client can obtain the target data corresponding to the at least two power stations in the data warehouse according to the power station identifications of at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format. The embodiment of the present specification adopts a self-developed data collection system to realize automatic data collection, and in the data collection process, customized data collection is realized by customizing data collection indicators. In addition, the embodiment of the present specification adopts a VPN tunnel for data transmission, which effectively prevents data leakage and illegal access, and is conducive to ensuring data security. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is an architecture diagram of a data processing system provided by one embodiment of this specification;

[0029] Figure 2 is a flow chart of a data processing method provided by an embodiment of this specification;

[0030] Figure 3 is a structural schematic diagram of a data processing device provided by an embodiment of this specification;

[0031] Figure 4 It is a structural block diagram of a computing device provided by an embodiment of this specification. DETAILED DESCRIPTION

[0032] Many specific details are described in the following description to facilitate a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the connotation of this specification, so this specification is not limited to the specific implementation disclosed below.

[0033] The terms used in one or more embodiments of this specification are only for the purpose of describing specific embodiments, and are not intended to limit one or more embodiments of this specification. The singular forms of "a", "said" and "the" used in one or more embodiments of this specification and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0034] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of this specification, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of this specification, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0035] First, the terms involved in one or more embodiments of this specification are explained.

[0036] Power Conversion System (PCS): also known as bidirectional energy storage inverter, is the core component that realizes the bidirectional flow of electric energy between the energy storage system and the power grid. It is used to control the charging and discharging process of the battery and perform AC / DC conversion.

[0037] Battery Management System (BMS): commonly known as a battery nanny or battery butler, it can be used to intelligently manage and maintain each battery unit, prevent the battery from overcharging and over-discharging, extend the battery life, and monitor the battery status.

[0038] Energy Management System (EMS): An intelligent system that integrates software and hardware to monitor, control and optimize energy flow and energy consumption in energy systems. Based on data acquisition, analysis and decision support technology, it can monitor the operating status of energy equipment, energy consumption and environmental conditions in real time, thereby achieving efficient management and optimization of energy.

[0039] Virtual Private Network (VPN): It can be understood as a virtual internal dedicated line of an enterprise. It can establish a dedicated communication line between two or more enterprise intranets located in different places connected to the network through a special encrypted communication protocol.

[0040] At present, for the multiple power stations that have been put into use, each power station is equipped with a set of master control screens that comprehensively display the basic information and operation data of the facilities in the station. However, if the detailed data of all power stations is needed to be conveniently viewed at a glance, the operation and maintenance personnel need to integrate the data of all power stations for comprehensive analysis and processing.

[0041] The traditional model is that each power station manually enters its own operating data into documents or spreadsheets, and compiles daily, weekly, and monthly operation and maintenance reports based on this. Subsequently, these reports need to be uploaded to the data analysis department of the headquarters step by step, and taken over by dedicated data processing personnel. They must collect reports from each power station one by one and carefully integrate them according to the power station and data category. This integration process involves combing a large amount of scattered data into comprehensive report data in a unified format that is easy to interpret. Only after completing this series of complicated manual summarization and organization can effective data display and in-depth analysis be truly carried out. Obviously, this traditional method has a lot of room for improvement in data flow efficiency, accuracy, and timeliness of decision support.

[0042] In this specification, a data processing system is provided. This specification also relates to a data processing method, a data processing apparatus, a computing device, a computer-readable storage medium, and a computer program, which are described in detail one by one in the following embodiments.

[0043] Figure 1 An architecture diagram of a data processing system provided according to an embodiment of the present specification is shown, specifically comprising: at least two first clients 102 and a second client 104;

[0044] The target client 102 is configured to determine the data collection index according to the point meter data of the power station, and collect the target data corresponding to the data collection index in the power station by running the data collection program, and transmit the target data and the power station identification of the power station to the data warehouse through the network tunnel for storage; wherein the target client 102 is each of the at least two first clients 102;

[0045] The second client 104 is configured to obtain target data corresponding to the at least two power stations in the data warehouse according to the power station identifiers of the at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format.

[0046] Specifically, the information point table of a power station is a summary table of specific points used to collect power station operation and monitoring data, and usually includes the following contents:

[0047] a. Equipment operation status point: the status point of the circuit breaker and knife switch (isolating switch), that is, the name of the switch knife switch and its auxiliary contacts;

[0048] b. Equipment operation parameter points: bus voltage (including phase voltage and line voltage), frequency; voltage, current, active power and reactive power of the power supply line; current of each load interval (the transformer can have the current on the high voltage side or both the high and low voltage sides), active power and reactive power; current of the busbar interval;

[0049] c. Equipment metering parameter points: active and reactive electric energy of the power supply line; active electric energy in the load interval, etc.

[0050] In actual applications, if the information point table contains the above content, it can meet the monitoring of power plant operation. However, in specific use, the data contained in the information point tables of different power plants may be different. For example, power plant 1 contains all the contents of a to c above, while power plant 2 and power plant 3 may only contain part of the contents of a to c above, that is, the point table data contained in the information point table of each power station is not exactly the same.

[0051] Based on this, in order to facilitate a quick and easy overview of the detailed data of all power stations, in an embodiment of the present specification, at least two first clients 102 first determine the data collection index based on the point table data of the power station, and collect and obtain the target data corresponding to the data collection index at the power station by running the data collection program, and transmit the target data and the power station identification of the power station to the data warehouse for storage through the network tunnel; the second client can obtain the target data corresponding to the at least two power stations in the data warehouse according to the power station identification of the at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format.

[0052] The data collection index may be determined according to the data content contained in the information point table. For example, if the information point table contains PCS-related data, the data collection index may be the PCS data reporting status.

[0053] The target data may be data related to the data collection index contained in the information point table; the network tunnel may be a VPN tunnel.

[0054] Since the multiple power stations put into use are distributed in different locations, each first client 102 can be used to collect target data of one or at least two power stations distributed in the same location. For example, power station 1 is deployed in Beijing, and power stations 2 and 3 are deployed in Guangzhou. Then, the target data of power station 1 can be collected through one first client 102, and the target data of power stations 2 and 3 can be collected through another first client 102. After the two first clients 102 transmit the collected target data to the data warehouse, the second client obtains the target data of all power stations from the data warehouse.

[0055] In the embodiments of this specification, the display screen is used to realize the real-time collection of key data of the power station and the effective capture of alarm information to ensure the integrity of data storage; the first client 102 is used to actively monitor the operating status and key parameters of the power station equipment, timely discover abnormal conditions and issue warnings to ensure the stable operation of the equipment. The second client 104 is responsible for receiving and storing the data collected by the first client 102 and the generated warning information to provide data support for subsequent analysis; the data and warning information received by the second client 104 can also be displayed through the display screen.

[0056] Specifically, the power station's collection equipment first stores the collected power station data in the information point table and displays it on the display screen in real time. Subsequently, the first client 102 can automatically connect to each power station through VPN, and capture relevant data items, i.e., data collection indicators, in real time according to preset requirements through the point table data stored in each power station. These data items can be flexibly configured to meet different monitoring requirements. Among them, the embodiment of this specification can perform data collection through an independently developed data collection program.

[0057] After the target data is successfully captured by the data collection program, the first client 102 can transmit the target data to the database of the first client 102 through the VPN tunnel, and then be classified and stored in the data warehouse to achieve persistent preservation. The storage period of data can be personalized according to its importance and urgency, ensuring that key data is retained for a long time, while secondary data can be cleaned up as needed.

[0058] Among them, the target data is classified and stored in the data warehouse. Specifically, in the data warehouse, the target data is classified and stored according to the power station. Specifically, the target data and the power station identification of the power station can be stored in association to identify the corresponding relationship between the target data and the power station.

[0059] After the target data is stored in the data warehouse, the second client 104 can perform statistical analysis on the target data in the data warehouse.

[0060] In the embodiments of this specification, the data statistics process is highly customized, and relevant data can be selected and extracted based on specific needs, and Python can be used to accurately capture the information required for data analysis. For example, if you need to analyze the CPU load and PCS data reporting status of the power station's acquisition equipment, you can specify the `system.cpu.util` and `system.pcs.data` indicators to obtain the target data of the two indicators `system.cpu.util` and `system.pcs.data` corresponding to each power station from the data warehouse, and then perform statistical analysis on the obtained target data.

[0061] Since the information point tables of each power station are different, the use of public version software or templates cannot meet the flexibility requirements of data collection. Therefore, the embodiment of this specification adopts a self-developed data collection system to realize automatic data collection, and in the data collection process, customized data collection is realized by customizing data collection indicators.

[0062] In addition, in order to ensure the security and stability of the target data during transmission, the embodiments of this specification use a VPN tunnel. Through the VPN tunnel, the self-developed data acquisition system can safely and reliably connect to each power station, capture data in real time and transmit it to the data warehouse. At the same time, the VPN tunnel also provides data encryption and identity authentication functions, effectively preventing data leakage and illegal access.

[0063] In an optional embodiment, the target client 102 is further configured to: collect target data corresponding to the data collection index within a preset time period in the power station by running a data collection program, and compare the number of collected target data with the preset number, and determine the communication status between the target client 102 and the power station according to the comparison result.

[0064] Specifically, the embodiments of this specification design a data quality monitoring mechanism to check the data quality according to the collection period (preset time period) and number of target data.

[0065] For example, the data collection indicator is the PCS data reporting status. When the first client 102 collects the target data corresponding to the indicator from the power station, it can calculate the number of target data reports according to the frequency of checking the target data reports once per minute. The target data is reported every 5 minutes, and the preset time period is one hour. Then the target data collected within one hour should be 12 items.

[0066] At the end of one hour (preset time period), check whether the number of reported target data reaches the preset 12±1 standard, and determine the communication status between the first client 102 and the power station based on the comparison result to ensure the accuracy and reliability of the target data collected by the first client 102.

[0067] In an optional embodiment, the target client 102 is further configured to: determine data collection indicators based on at least two fields contained in the information point table of the power station, and obtain target data corresponding to the data collection indicators within a preset time period at the power station by running a data collection program, and write the target data and the power station identifier of the power station into a temporary file.

[0068] In an optional embodiment, the target client 102 is further configured to: call an analysis function to read the target data corresponding to the power station identifier in the temporary file, determine the number of target data items by traversing the target data, and compare the number of target data items with a preset number, and when it is determined according to the comparison result that the number of target data items is less than the preset number, determine that the communication status between the target client 102 and the power station is abnormal; or, when it is determined according to the comparison result that the number of target data items is equal to the preset number, determine that the communication status between the target client 102 and the power station is normal, and transmit the target data and the power station identifier of the power station to the data warehouse through a network tunnel for storage.

[0069] Specifically, since the information point tables of each power station are not the same, that is, the fields contained in the information point tables of each power station are not the same, in order to be able to conveniently view the detailed data of all power stations, the embodiment of this specification customizes the data collection indicators, and uses the data corresponding to at least two fields in the information point table related to the data collection indicators as the target data corresponding to the data collection indicators to realize the integration of the point table data, thereby realizing the use of the same fields to represent the point table data of each power station, that is, to achieve the unification of the fields of each information point table.

[0070] In addition, in addition to at least two fields in the information point table, the data collection indicator may also add other fields according to actual needs, which is not limited here.

[0071] For example, if the data collection indicator is the PCS data reporting status, it is necessary to collect relevant data of the PCS in the power station to perform statistical analysis on the indicator. If the PCS-related fields contained in the information point table of power station 1 are PCS name and PCS status, then the custom data collection indicator written by shell can be composed of "PCS name-PCS status-reported data-reporting time", among which PCS name and PCS status are fields contained in the information point table, and reported data and reporting time are fields added according to needs.

[0072] After determining the data collection indicators, the data collection indicators can be specifically formed into a JSON string, and then the target data corresponding to the data collection indicators within a preset time period can be obtained at the power station by running an independently developed data collection program, and the target data and the power station identification of the power station can be written into a temporary file data_temp.xxx.

[0073] After writing is completed, the temporary file is passed to the next analysis function, which reads the target data corresponding to the power station identification stored in the temporary file and traverses each string in a loop to determine the number of strings.

[0074] As mentioned above, in the process of collecting target data corresponding to the data collection indicators from the power station, the first client 102 can calculate the number of reported target data at a frequency of checking the number of reported target data once per minute. The target data is reported once every 5 minutes, and at the end of one hour (preset time period), it is checked whether the number of reported target data reaches the preset standard of 12±1, and the communication status between the first client 102 and the power station is determined based on the comparison results to ensure the accuracy and reliability of the target data collected by the first client 102.

[0075] Among them, when it is determined according to the comparison result that the number of target data is less than the preset standard of 12±1, it is determined that the communication status between the first client 102 (target client 102) and the power station is abnormal, and the information of the abnormal communication status can be sent to the second client 104 for early warning information display; or, when it is determined according to the comparison result that the number of target data is equal to the preset standard of 12±1, it is determined that the communication status between the first client 102 and the power station is normal, and then the target data and the power station identifier of the power station can be transmitted to the data warehouse through the VPN tunnel for storage.

[0076] In addition, when the number of target data is determined to be greater than the preset standard of 12±1 according to the comparison results, it can also be determined that the communication status between the first client 102 and the power station is abnormal, and the information about the abnormal communication status can be sent to the second client 104 for early warning information display.

[0077] The embodiments of this specification use a custom data collection program, which can check the data quality according to the collection period and number of each data set to prevent underreporting and overreporting of data, which will affect the authenticity of subsequent data display.

[0078] In an optional embodiment, the second client is further configured to: obtain, according to the power station identifications of at least two power stations, first target data of the first time interval and second target data of the second time interval corresponding to the at least two power stations in the data warehouse, respectively, perform statistical analysis on the first target data and the second target data, generate first analysis results and second analysis results, and display the first analysis results in a first display format, and display the second analysis results in a second display format.

[0079] In an optional implementation, the first time interval includes a current time interval, and the second time interval includes a historical time interval; the first display form includes a pie chart form, and the second display form includes a curve chart form.

[0080] Specifically, the first time interval may be the current time interval, and the current time interval may be an interval formed by the start time of the date to which the current time belongs and the current time. For example, if the current time is 10:00 and the date to which the current time belongs is 2024-07-20, then the current time interval may be 00:00 to 10:00 of 2024-07-20.

[0081] The second time interval may be a historical time interval, and the historical time interval may be an interval consisting of a period of time before the current time interval. For example, if the current time interval is 00:00 to 10:00 on 2024-07-20, then the historical time interval may be 00:00 on 2024-01-01 to 23:59 on 2024-07-19.

[0082] After the first client 102 stores the target data and the power station identification in the data warehouse, the second client 104 can read the target data of each power station in the data warehouse, and classify the target data according to the current time interval and the historical time interval, and then perform statistical analysis on the target data of the current time interval and the target data of the historical time interval respectively. For the target data of the historical time interval, the performance change trend of the acquisition equipment of the power station can be specifically statistically analyzed; for the target data of the current time interval, the abnormal power stations in each power station can be specifically statistically analyzed.

[0083] After obtaining the analysis results, the statistical results of the target data in the historical time interval can be presented in the form of a curve chart, that is, the target data of the historical time interval of each power station is presented through an independent curve chart, which is convenient for tracking the performance change trend of the power station's acquisition equipment; for the target data in the current time interval, it can be presented in the form of a pie chart to quickly identify the proportion of abnormal power stations in the total number of power stations. In addition, the system can also obtain information such as abnormal time and abnormal proportion based on the abnormal status word, providing strong support for power station operations.

[0084] In addition, statistical analysis is performed on the abnormal power stations among the power stations. Specifically, whether the power station is normal can be determined based on the communication status between the first client 102 and the power station. The number of target data items can be compared with the preset number. If the number of target data items is less than or greater than the preset number, it is determined that the communication status between the first client 102 and the power station is abnormal, that is, the power station is determined to be an abnormal power station; or, if the number of target data items is equal to the preset number, it is determined that the communication status between the first client 102 and the power station is normal, that is, the power station is determined to be a normal power station.

[0085] In actual applications, since power stations usually use EMS, BMS and other collection devices to collect data from power stations, in the embodiments of this specification, for the target data in the current time interval, in addition to statistically analyzing the power stations with abnormalities in each power station, the number of collection devices with abnormalities in each power station can also be statistically analyzed. If it is determined that a power station is abnormal, all collection devices in the power station can be determined as abnormal. Then, when displaying, they can be presented in the form of a pie chart to quickly identify the proportion of abnormal collection devices in the total number of collection devices.

[0086] Compared with the traditional implementation method, the data processing system provided in the embodiment of this specification has the following advantages:

[0087] (1) Security: The embodiments of this specification have designed a set of measures that do not rely on any third-party environment, eliminating the need for direct operation of the core server password or database password. Users only need to edit the corresponding data capture rules according to actual monitoring needs. No passwords need to be manually configured during the data collection process. As long as the network connection is unobstructed, the system can work normally, which significantly reduces the potential risk of password leakage, and the transmission uses a VPN encrypted tunnel to increase the security of the transmission.

[0088] (2) Efficiency: With a one-time development investment, the system realizes an automated process that runs continuously. Once the monitoring requirements are set, the entire process from data collection, storage to aggregation and display will be automatically executed, eliminating the reliance on manual operations in the traditional model, such as manually aggregating power plant data and processing it in the data center. This automated mechanism greatly improves the speed of identifying and processing abnormal data by more than 90% compared to before, significantly enhancing data processing efficiency.

[0089] (3) Practicality: The embodiments of this specification realize automated data monitoring, eliminating the need for manual monitoring, thereby significantly improving work efficiency. It supports almost real-time data monitoring, quickly summarizes and displays collected data, and has a built-in early warning mechanism that can automatically generate alarms regularly to ensure timely response to potential problems. In addition, the system maintains complete data archiving to facilitate future data tracing and statistical analysis.

[0090] In addition, the embodiment of the present specification can also be that the master control server sends the target probe to at least two first clients 102 through a preset port; the target client 102 determines the communication address associated with the target container by running the target probe, and detects the communication status between the data acquisition device corresponding to the communication address and the target container, generates corresponding detection results and returns them to the master control server, wherein the target container is each of the at least two containers deployed by the target client 102; the master control server sends the detection results to the second client 104, wherein the detection results are used for display by the second client 104.

[0091] Specifically, the probe is a script program; the container deployed by the target client 102 may be a docker container, and at least two docker containers may be deployed in each target client 102; the communication address may be an IP address; the data acquisition device may be an EMS device and a BMS device, the EMS device is used to collect device data of energy equipment in the power station, the BMS device is used to collect battery data (battery cell data) of batteries in the power station, and each power station may include at least two EMS devices and BMS devices; each docker container may be used to collect data collected by multiple EMS devices and / or multiple BMS devices.

[0092] In actual applications, the Docker container can automatically collect data according to a preset period. For example, the preset period can be one minute, but it can be set according to actual needs and is not limited here.

[0093] In the embodiment of this specification, each target client 102 can be deployed on the VPN of the same network segment, that is, the target probe of the master control server can be VPN-connected to each target client 102 through the same network segment. The whole formed by each target client 102 can be regarded as a virtual cluster and included in the control of the master control server.

[0094] In actual applications, the master control server can be used to periodically call the target probe to detect the data of each target client 102. Specifically, the master control server can send the target probe to each target client 102 through a preset port. Each target client 102 determines one or at least two IP addresses associated with each container deployed in the target client 102 by running the target probe. Each IP address corresponds to an EMS device or BMS device. The association between the container and the IP address indicates that the container is used to collect data of the EMS device or BMS device corresponding to the IP address.

[0095] Taking one of the target containers as an example, after determining the IP address associated with the target container, the communication status between the EMS device and / or BMS device corresponding to the IP address and the target container can be detected, and the corresponding detection result can be generated and returned to the master control server.

[0096] The master control server is used to receive the communication status detection results returned by each target client 102 in the virtual cluster, and send them to the second client 104. The second client 104 can summarize and display each communication status detection result.

[0097] In addition, the target probe can also be used to detect the communication status between each container on the target client 102 and the target client 102 . The target client 102 can also return the detection result to the master control server, and the master control server sends it to the second client 104 .

[0098] In actual applications, the second client 104 can collect various detection results into Zabbix for monitoring, and can display specific monitoring results in a visual interface. According to the monitoring results, it can be determined whether the communication status between each container and the data acquisition device is normal, whether the communication status between each container and the target client 102 is normal, and indicators such as the duration of the abnormality can be determined. When it is determined that an abnormality exists, abnormal alarm processing can also be performed.

[0099] In the embodiments of this specification, since the environment of the docker container is relatively closed, this is an advantage of its ability to run independently. However, because its environment is isolated from the host machine and for security reasons, generally only the corresponding business ports are opened, the environments of each docker container are also isolated from each other. This makes the communication management between each container and each data acquisition device extremely cumbersome. The embodiments of this specification, by adding probes for communication monitoring, achieve automatic monitoring of the communication status between the container and the data acquisition device and abnormal alarm without affecting the collection and transmission efficiency of the power station data.

[0100] The embodiments of this specification do not require the installation of a third-party dependent environment, do not require additional exposure of the core collection container's ports, and do not require data analysis in the program running environment, which greatly ensures the security and stability of the battery cell data and device data.

[0101] Alternatively, the target client 102 determines the process to be detected corresponding to the target container in response to the communication status detection instruction sent by the master control server, wherein the target container is each of the at least two containers, and the process to be detected is used to obtain data collected by the data acquisition device, and then reads the message to be detected corresponding to the process to be detected in the target container; compares the message to be detected with the standard message, and generates a detection result of the communication status corresponding to the process to be detected based on the comparison result, wherein the communication status is used to characterize the communication status between the target container and the data acquisition device; and then sends the detection result to the master control server, wherein the detection result is used for display by the master control server.

[0102] Specifically, since the target container can be used to obtain data collected by multiple data acquisition devices, before obtaining the data of each data acquisition device, the process to be detected corresponding to each data acquisition device can be created first. After the creation is completed, the number of data acquisition devices communicating with the target container is equal to the number of processes to be detected in the target container, that is, the target container is used to obtain data from several data acquisition devices, that is, there are several processes to be detected, and each process to be detected corresponds to each data acquisition device one by one. For each process to be detected, its corresponding process number can be determined according to the order in which each process is created, and "tc+process number" can be used as its process identifier.

[0103] In addition, a communication status detection instruction can be sent by the master control server to the target client 102, wherein the master control server sends a communication status detection instruction to the target client 102 by running the container management program, and the instruction is used to instruct the target client 102 to detect the communication status between the container deployed in the target client 102 and the data acquisition equipment deployed in the power station.

[0104] After receiving the communication status detection instruction, the target client 102 responds to the communication status detection instruction and determines the process to be detected corresponding to the target container.

[0105] In actual application, as mentioned above, at least two containers are deployed in the target client 102, and the target container is each of the at least two containers. Therefore, the target client 102 can obtain the IDs of all running docker containers in the target client 102, and store these IDs in the variable container_ids. Then, for each container ID in container_ids, that is, each target container, its corresponding process to be detected can be determined.

[0106] The message to be detected is a message generated by data transmission between the target container and the data acquisition device corresponding to the process to be detected.

[0107] In the embodiment of this specification, after determining the process to be detected corresponding to the target container, the message to be detected corresponding to each process to be detected can be read in the target container, so as to facilitate subsequent analysis of the message to be detected to determine the communication status between the target container and the data acquisition device.

[0108] After reading the messages to be detected corresponding to each process to be detected, each message to be detected can be compared with the standard message to determine whether the data collected by the process to be detected is accurate or complete based on the accuracy of the message to be detected, thereby further judging whether the communication status between the target container and the data acquisition device is normal.

[0109] In practical applications, the standard message is the format of the correct message. Comparing the message to be detected with the standard message is equivalent to checking the message to be detected to determine whether the message to be detected is a correct message.

[0110] For example, the standard message may be composed of two hexadecimal digits, where each two digits constitute one byte. If the eighth byte in the standard message is ac, then it is necessary to determine whether the eighth byte in the message to be detected is ac.

[0111] After comparing each byte in the message to be detected with the corresponding byte in the standard message, a detection result of the communication state corresponding to the process to be detected can be generated based on the comparison result.

[0112] After the detection results of the communication status corresponding to each process to be detected are generated, they can be sent to the master control server, which will display the detection results.

[0113] The embodiments of this specification do not need to enter the container. The scheduler traverses each container, calls the message detection program in the container to obtain the message, and then performs message comparison. After all the processes to be detected are processed, use the pkill command to terminate the message detection process in the container. In addition, by managing the reading of container messages through the scheduler, access rights can be strictly controlled, allowing only authorized users to access and operate message data to ensure data security.

[0114] In actual applications, the power station in the embodiments of this specification can be used to supply power to an electric locomotive, the electric locomotive includes a battery storage vehicle and a traction vehicle, the battery storage vehicle includes a battery storage module and a pantograph, the traction vehicle includes multiple battery packs, and the traction vehicle is connected to the battery storage vehicle; the battery storage vehicle is used to determine the remaining power of the battery storage vehicle and the traction vehicle, determine the charging information of the battery storage vehicle and the traction vehicle according to the remaining power and the power to be consumed by the electric locomotive, and send a charging instruction to the power station based on the charging information; the power station is used to charge the battery storage vehicle and / or the traction vehicle through the pantograph in response to the charging instruction.

[0115] Specifically, in the electric locomotive provided in the embodiment of this specification, the front of the locomotive is a battery storage car, and the battery storage car is connected to a tractor. The tractor is composed of a flatbed truck and a container loaded on the flatbed truck, and a plurality of battery packs are installed in the container. The battery storage car and the flatbed truck can be physically connected, for example, by a hook connection, and the battery storage car and the battery pack can be electrically connected, for example, by a cable connection, so as to realize electrical communication between the battery storage car and the tractor. In practical applications, the battery storage module of the battery storage car and the battery pack in the tractor can both be used as the power source of the electric locomotive to provide power for the electric locomotive. Among them, the battery storage module can be a storage battery, and the battery pack can be composed of lithium batteries.

[0116] In addition, power stations can be set up on both sides of the route of the electric locomotive to stop and charge the electric locomotive when passing through the power station. The location and number of power stations can be determined according to actual needs and are not limited here. In addition, the other end of the tractor can also be connected to a truck. The truck is also composed of a flatbed truck and a container. The difference from the tractor is that the container of the truck is used to load goods.

[0117] A pantograph is provided above the electric storage car. When the electric locomotive needs to be charged by a power station, the pantograph can be controlled to rise so as to contact the power station. The power station charges the electric locomotive through the pantograph. After charging is completed, the pantograph can be controlled to fall.

[0118] When the electric locomotive is driving, the battery storage vehicle can determine the remaining power of the battery storage vehicle and the traction vehicle through the energy storage system, that is, determine the remaining power of the battery storage module and multiple battery packs, and then determine the charging information of the battery storage vehicle and the traction vehicle based on the remaining power and the power to be consumed by the electric locomotive. The charging information includes but is not limited to the power to be charged, charging priority, charging current and / or charging voltage, etc., specifically, determine the information such as the power to be charged, charging priority, and charging current and voltage of the battery storage vehicle and the traction vehicle; after the determination is completed, when the electric locomotive drives to the power station, it can send a charging instruction to the power station based on the charging information, and control the pantograph to raise the pantograph so that the pantograph contacts the power station, so that the power station charges the battery storage vehicle and / or the traction vehicle through the pantograph.

[0119] Alternatively, in the case that the traction vehicle is low on power, a signal is sent to separate the storage vehicle and the low-power traction vehicle in the preset battery replacement operation area of ​​the power station, so that the storage vehicle can continue to travel across the switch based on the battery storage module; a signal is received to enter the dedicated charging line, and a signal is sent to the storage vehicle to enter the preset dedicated charging line and connect with the fully-charged traction vehicle, and the preset switch is switched, so that the fully-charged traction vehicle supplies power to the storage vehicle; after the storage vehicle is connected with the fully-charged traction vehicle, a signal is sent to the storage vehicle to exit the dedicated charging line and connect with the low-power traction vehicle, so that the storage vehicle pulls the fully-charged traction vehicle and the low-power traction vehicle into the dedicated charging line; on the dedicated charging line, a signal is sent to the storage vehicle to separate from the low-power traction vehicle, leaving the low-power traction vehicle in the dedicated charging line for charging, and waiting for the next battery replacement after it is fully charged.

[0120] Among them, the distance between the preset dedicated charging line and the power plant and the locomotive running track is respectively within a first preset distance range and a second preset distance range; the under-powered traction vehicle is left on the dedicated charging line for charging, specifically, the grid load of the power plant is monitored in real time, and when the grid load is less than or equal to the preset load value, the under-powered traction vehicle left on the dedicated charging line is used as an energy storage device to charge the under-powered traction vehicle; when the grid load is greater than the preset load value, the fully charged traction vehicle in the dedicated charging line is used as a backup battery to perform peak and valley regulation for the power plant.

[0121] In addition, the time periods corresponding to the highest and lowest points of the power plant's grid load curve in historical data can also be obtained; the time periods corresponding to the highest and lowest points of the power grid load curve in a day are used as the locomotive battery replacement limit time and the optimal battery replacement time, respectively, wherein during the locomotive battery replacement limit time, no less than a preset number of under-powered traction vehicles stay on the dedicated charging line.

[0122] Furthermore, the time periods corresponding to the highest and lowest points of the power grid load curve of the power plant in the historical data are obtained. Specifically, the power grid load curve of the power plant on each day of multiple preset years is used as historical data to predict the power grid load curve of each day in the next year; according to the power grid load prediction curve of each day, the time periods corresponding to the highest and lowest points of the power grid load prediction curve of each day are determined.

[0123] According to the grid load forecast curve for each day, determine the time periods corresponding to the highest point and the lowest point of the grid load forecast curve for each day. Specifically, in the grid load forecast curve for each day, determine the first front balance point and the first rear balance point with the smallest absolute value of the time difference with the highest point before and after the highest point, respectively, and determine the second front balance point and the second rear balance point with the smallest absolute value of the time difference with the lowest point before and after the lowest point, respectively, wherein the balance point is the point where the grid load is the power generation of the power plant; the time period between the first front balance point and the first rear balance point is taken as the time period corresponding to the highest point in a day; the time period between the second front balance point and the second rear balance point is taken as the time period corresponding to the lowest point in a day.

[0124] In addition, the locomotive battery replacement schedule can be determined based on the locomotive battery replacement limit time and the optimal battery replacement time, so as to peak and valley adjust the power plant through the traction vehicle of the locomotive battery replacement.

[0125] In practical applications, the power-on and power-off control environment data and the high-voltage system status data can be obtained through the sensor network, and the battery abnormal interference index of the electric locomotive can be obtained by comprehensive analysis. According to the battery abnormal interference index of the electric locomotive, the battery cluster abnormality assessment threshold is processed; the abnormal status data of each battery unit of the electric locomotive is monitored, and the battery cluster abnormality assessment value of the electric locomotive is obtained by comprehensive analysis; the battery cluster abnormality assessment value of the electric locomotive is compared with the battery cluster abnormality assessment threshold. If the battery cluster abnormality assessment value of the electric locomotive is greater than the battery cluster abnormality assessment threshold, the electric locomotive is powered off.

[0126] Specifically, a comprehensive analysis is performed to obtain the abnormal battery interference index of the electric locomotive. The specific analysis process is: deploy a number of environmental monitoring points, collect the ambient temperature, ambient humidity and ambient air pressure of each environmental monitoring point, and obtain the reference suitable ambient temperature, reference suitable ambient humidity and reference suitable ambient air pressure from the electric locomotive database, and obtain the upper and lower power control environment abnormality assessment value after processing.

[0127] In a specific embodiment, the abnormal evaluation value of the power-on / off control environment is used to quantitatively evaluate the abnormal degree of the power-on / off control environment, and provide a data basis for power-on / off control. The abnormal evaluation value of the power-on / off control environment is related to the ambient temperature, ambient humidity, and ambient air pressure. The more the ambient temperature, ambient humidity, and ambient air pressure deviate from the corresponding reference suitable index, the larger the abnormal evaluation value of the power-on / off control environment is, indicating that the power-on / off control environment is more abnormal.

[0128] It should be understood that in this embodiment, the environmental monitoring points are deployed to monitor the power-on and power-off control environmental data. Power-on and power-off control refers to the process management of opening (powering on) and closing (powering off) the high-voltage electrical system of the electric locomotive. This process involves the orderly power-on and power-off of multiple high-voltage components of the vehicle to ensure the safety and efficiency of the operation.

[0129] The power-on process refers to starting the entire electrical system and ensuring that each subsystem is activated in a predetermined order to prepare for vehicle operation, including waking up the BMS (Battery Management System) to monitor the battery status, activating the MCU (Microcontroller Unit) to control the motor, and safely closing the high-voltage contactor through the pre-charging circuit so that the high-voltage battery can supply power to the vehicle's high-voltage system.

[0130] The power-off process refers to the control process of system shutdown, including gradually shutting down high-voltage loads, disconnecting high-voltage power supplies, performing necessary safety checks and energy release, and ultimately allowing the entire high-voltage system to safely enter a non-working state.

[0131] Specifically, the electric locomotive is powered off, including power off control when only the auxiliary equipment on the locomotive is powered on. The specific process is: the battery management system sends a locomotive power-off request instruction, the locomotive auxiliary equipment sends a power-off signal three times in a row or the wake-up signal is lost, the secondary master control will receive these signals and immediately send a water cooling shutdown instruction.

[0132] The battery management system detects the total current of the loop, powers off the high voltage according to the current size, and disconnects the total positive relay and the total negative relay in the battery cluster in turn. All battery clusters complete the high voltage power-off synchronously.

[0133] By collecting key operating parameters of batteries and high-voltage systems in real time, a detailed data basis is provided for the accurate evaluation of battery status, and battery abnormalities are dynamically evaluated, which improves the pertinence and accuracy of judgments. At the same time, it also provides data support for optimizing energy management and improving endurance, thereby promoting the overall performance of electric locomotives.

[0134] In the embodiment of this specification, the target client 102 first determines the data collection index according to the point table data of the power station, and collects the target data corresponding to the data collection index in the power station by running the data collection program, and transmits the target data and the power station identification of the power station to the data warehouse for storage through the network tunnel; the second client 104 can obtain the target data corresponding to the at least two power stations in the data warehouse according to the power station identifications of at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format. The embodiment of this specification adopts a self-developed data collection system to realize automatic data collection, and in the data collection process, customized data collection is realized by customizing data collection indicators. In addition, the embodiment of this specification adopts a VPN tunnel for data transmission, which effectively prevents data leakage and illegal access, and is conducive to ensuring data security.

[0135] Figure 2 A flow chart of a data processing method provided according to an embodiment of the present specification is shown, which specifically includes the following steps.

[0136] Step 202: determining a data collection index according to the point meter data of the power station, and acquiring target data corresponding to the data collection index in the power station by running a data collection program.

[0137] Step 204: Transmit the target data and the power station identification of the power station to a data warehouse for storage via a network tunnel.

[0138] Step 206: acquiring target data respectively corresponding to the at least two power stations in the data warehouse according to the power station identifiers of the at least two power stations.

[0139] Step 208: Perform statistical analysis on the target data corresponding to the at least two power stations, and present the analysis results in a preset presentation format.

[0140] Specifically, the data collection index may be determined according to the data content contained in the information point table. For example, if the information point table contains PCS-related data, the data collection index may be the PCS data reporting status.

[0141] The target data may be data related to the data collection index contained in the information point table; the network tunnel may be a VPN tunnel.

[0142] The information point table of a power station is a summary table of specific points used to collect power station operation and monitoring data, which usually includes data such as equipment operation status points, equipment operation parameter points, and equipment metering parameter points.

[0143] In actual applications, if the information point table contains the above content, it can meet the monitoring of power plant operation. However, in specific use, the data contained in the information point tables of different power plants may be different, that is, the point table data contained in the information point tables of each power plant are not exactly the same.

[0144] Based on this, in order to conveniently view the detailed data of all power stations, in the embodiment of this specification, the power station collection equipment first stores the collected power station data in the information point table and displays it on the display screen in real time. Subsequently, the relevant data items, i.e., data collection indicators, can be captured in real time according to preset requirements through the point table data stored in each power station.

[0145] After the target data is successfully captured by the data collection program, it can be transmitted to the data warehouse through the VPN tunnel for classified storage to achieve persistent preservation.

[0146] In addition, the data processing method provided in the embodiments of this specification can be applied to the client. Since the multiple power stations in use are distributed in different locations, each client can be used to collect target data of one or at least two power stations distributed in the same location. After each client collects and obtains the target data, it will be transmitted to the data warehouse for storage. Therefore, each client can also obtain the target data of all power stations from the data warehouse and perform statistical analysis and display.

[0147] The embodiments of this specification determine the data collection index according to the point table data of the power station, and collect the target data corresponding to the data collection index at the power station by running the data collection program, transmit the target data and the power station identification of the power station to the data warehouse for storage through the network tunnel, obtain the target data corresponding to the at least two power stations in the data warehouse according to the power station identification of at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format. The embodiments of this specification use a self-developed data collection system to realize automatic data collection, and in the data collection process, customized data collection is realized by customizing data collection indicators. In addition, the embodiments of this specification use a VPN tunnel for data transmission, which effectively prevents data leakage and illegal access, and is conducive to ensuring data security.

[0148] The above is a schematic scheme of a data processing method of this embodiment. It should be noted that the technical scheme of the data processing method and the technical scheme of the above data processing system belong to the same concept, and the details not described in detail in the technical scheme of the data processing method can be referred to the description of the technical scheme of the above data processing system.

[0149] Corresponding to the above method embodiment, this specification also provides a data processing device embodiment, Figure 3 FIG. 1 is a schematic diagram showing the structure of a data processing device provided by an embodiment of the present specification. Figure 3 As shown, the device comprises:

[0150] The collection module 302 is configured to determine a data collection index according to the point meter data of the power station, and collect target data corresponding to the data collection index in the power station by running a data collection program;

[0151] The transmission module 304 is configured to transmit the target data and the power station identification of the power station to a data warehouse for storage through a network tunnel;

[0152] An acquisition module 306 is configured to acquire target data corresponding to the at least two power stations respectively in the data warehouse according to the power station identifiers of the at least two power stations;

[0153] The display module 308 is configured to perform statistical analysis on the target data corresponding to the at least two power stations respectively, and display the analysis results in a preset display format.

[0154] The above is a schematic scheme of a data processing device of this embodiment. It should be noted that the technical scheme of the data processing device and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the data processing device can be referred to the description of the technical scheme of the above data processing method.

[0155] Figure 4 The block diagram of a computing device 400 according to one embodiment of the present specification is shown. The components of the computing device 400 include but are not limited to a memory 410 and a processor 420. The processor 420 is connected to the memory 410 via a bus 430, and the database 450 is used to store data.

[0156] The computing device 400 also includes an access device 440 that enables the computing device 400 to communicate via one or more networks 460. Examples of these networks include a public switched telephone network (PSTN), a local area network (LAN), a wide area network (WAN), a personal area network (PAN), or a combination of communication networks such as the Internet. The access device 440 may include one or more of any type of network interface (e.g., a network interface card (NIC)) wired or wireless, such as an IEEE 802.11 wireless local area network (WLAN) wireless interface, a World Wide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a universal serial bus (USB) interface, a cellular network interface, a Bluetooth interface, a near field communication (NFC) interface, and the like.

[0157] In one embodiment of the present specification, the above components of the computing device 400 and Figure 4 Other components not shown in the figure may also be connected to each other, for example, via a bus. It should be understood that Figure 4 The computing device structure block diagram shown is only for the purpose of illustration, and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0158] Computing device 400 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.), or other types of mobile devices, or a stationary computing device such as a desktop computer or PC. Computing device 400 may also be a mobile or stationary server.

[0159] The processor 420 is used to execute the following computer executable instructions, which implement the steps of the above data processing method when executed by the processor.

[0160] The above is a schematic scheme of a computing device of this embodiment. It should be noted that the technical scheme of the computing device and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the computing device can be referred to the description of the technical scheme of the above data processing method.

[0161] An embodiment of the present specification further provides a computer-readable storage medium storing computer-executable instructions, which can implement the steps of the above-mentioned data processing method when executed by a processor.

[0162] The above is a schematic scheme of a computer-readable storage medium of this embodiment. It should be noted that the technical scheme of the storage medium and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the storage medium can be referred to the description of the technical scheme of the above data processing method.

[0163] An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer is caused to execute the steps of the above-mentioned data processing method.

[0164] The above is a schematic scheme of a computer program of this embodiment. It should be noted that the technical scheme of the computer program and the technical scheme of the above data processing method belong to the same concept, and the details not described in detail in the technical scheme of the computer program can be referred to the description of the technical scheme of the above data processing method.

[0165] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0166] The computer instructions include computer program codes, which may be in source code form, object code form, executable files or some intermediate forms, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0167] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the embodiments of this specification are not limited by the order of the actions described, because according to the embodiments of this specification, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the embodiments of this specification.

[0168] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0169] The preferred embodiments of this specification disclosed above are only used to help explain this specification. The optional embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of the embodiments of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the embodiments of this specification, so that technicians in the relevant technical field can well understand and use this specification. This specification is only limited by the claims and their full scope and equivalents.

Claims

1. A data processing system, comprising: at least two first clients and a second client; A target client is configured to determine a data collection index according to the point meter data of the power station, and to collect target data corresponding to the data collection index at the power station by running a data collection program, and to transmit the target data and the power station identifier of the power station to a data warehouse through a network tunnel for storage; wherein the target client is each of the at least two first clients; The second client is configured to obtain the target data corresponding to the at least two power stations in the data warehouse according to the power station identifiers of the at least two power stations, perform statistical analysis on the target data corresponding to the at least two power stations, and display the analysis results in a preset display format.

2. According to the data processing system of claim 1, the target client is also configured to: collect target data corresponding to the data collection index within a preset time period in the power station by running a data collection program, and compare the number of collected target data with the preset number, and determine the communication status between the target client and the power station according to the comparison result.

3. According to the data processing system of claim 1, the target client is further configured to: determine the data collection index based on at least two fields contained in the information point table of the power station, and obtain the target data corresponding to the data collection index within a preset time period in the power station by running the data collection program, and write the target data and the power station identification of the power station into a temporary file.

4. According to the data processing system of claim 3, the target client is further configured to: call the analysis function to read the target data corresponding to the power station identifier in the temporary file, determine the number of target data by traversing the target data, and compare the number of target data with a preset number, and when it is determined according to the comparison result that the number of target data is less than the preset number, determine that the communication status between the target client and the power station is abnormal; or, when it is determined according to the comparison result that the number of target data is equal to the preset number, determine that the communication status between the target client and the power station is normal, and transmit the target data and the power station identifier of the power station to the data warehouse through the network tunnel for storage.

5. According to the data processing system of claim 1, the second client is further configured to: obtain, according to the power station identifications of at least two power stations, first target data of the first time interval and second target data of the second time interval corresponding to the at least two power stations in the data warehouse, respectively, perform statistical analysis on the first target data and the second target data, generate first analysis results and second analysis results, and display the first analysis results in a first display format, and display the second analysis results in a second display format.

6. The data processing system according to claim 5, wherein the first time interval includes a current time interval, and the second time interval includes a historical time interval; the first display form includes a pie chart form, and the second display form includes a curve chart form.

7. A data processing method, comprising: Determine a data collection index according to the point meter data of the power station, and collect target data corresponding to the data collection index at the power station by running a data collection program; Transmitting the target data and the power station identifier of the power station to a data warehouse for storage through a network tunnel; Acquire target data corresponding to the at least two power stations respectively in the data warehouse according to the power station identifiers of the at least two power stations; Statistical analysis is performed on the target data corresponding to the at least two power stations, and the analysis results are displayed in a preset display format.

8. A data processing device, comprising: A collection module is configured to determine a data collection index according to the point meter data of the power station, and collect target data corresponding to the data collection index in the power station by running a data collection program; a transmission module, configured to transmit the target data and the power station identification of the power station to a data warehouse for storage through a network tunnel; an acquisition module, configured to acquire target data respectively corresponding to the at least two power stations in the data warehouse according to power station identifiers of the at least two power stations; The display module is configured to perform statistical analysis on the target data corresponding to the at least two power stations respectively, and display the analysis results in a preset display format.

9. A computing device comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the communication management method described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the communication management method according to any one of claims 1 to 6.

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