Electric quantity data acquisition method, device, equipment and medium

Abstract

The invention discloses an electric quantity data acquisition method, device and equipment and a medium, and the electric quantity data acquisition method automatically obtains electric energy meter data through an electric energy acquisition device, replaces manual meter reading, and improves the data accuracy and real-time performance. Daily electric quantity statistical data is generated through analysis and algorithm processing and is written into a management database through a secure transmission mechanism, so that data integrity and network security are guaranteed. Through a webpage publishing mechanism, remote online checking of electric quantity information in an industrial network by an authorization terminal is realized, and an information island is broken. And finally, an abnormity monitoring mechanism is introduced, real-time early warning is carried out on electric quantity abrupt change, transformer loss abnormity and other situations, and a metering loop fault is found in time. According to the method, full-chain automatic, visual and intelligent management and control of the electric quantity data are realized, and the operation safety and efficiency of the nuclear power station are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of power plant data processing technology, and in particular to a method, apparatus, equipment and medium for acquiring power data. Background Technology

[0002] In the operation and management of nuclear power plants, electricity data is the core basis for measuring the generating capacity of the units, calculating energy efficiency, and reporting power production status to the grid. Accurate and timely acquisition and reporting of electricity data are of great significance for ensuring the stable operation of the power system, optimizing energy dispatch, and improving the operating efficiency of the power plant.

[0003] Traditional nuclear power plant electricity data collection primarily relies on manual operation. Operators must travel to the high-altitude platforms of the ultra-high-voltage switchyard and electrical building at a set time each morning to read electricity meters and obtain data on the power generation and grid connection of each unit. Subsequently, the shift supervisor manually compiles the data from the four units and reports the previous day's electricity data to the power grid dispatch center before 1:00 AM daily. This necessitates operators repeatedly performing on-site meter reading tasks every night, resulting in a significant long-term drain on manpower and hindering staff reduction and efficient operation. Furthermore, the manual reading and statistical process relies on paper records or manual input, posing risks of data omissions and transcription errors, affecting data accuracy. In addition, although some power plants have deployed electricity workstations and power acquisition systems, the collected data is often limited to local viewing and lacks effective integration with industrial information networks, as well as remote access and automatic early warning functions. Therefore, existing electricity data collection methods are insufficient to meet the higher requirements of nuclear power plants for intelligent, automated, and safe operation. An alternative electricity data collection method is urgently needed to address the technical challenges of current power plant electricity data collection methods failing to meet the demands for further intelligent and safe operation. Summary of the Invention

[0004] The embodiments of the present invention provide a method, apparatus, device and medium for acquiring power data, which aims to solve the technical problem that the existing power data acquisition methods for power plants cannot meet the needs of power plants for further intelligent and safe operation.

[0005] In a first aspect, embodiments of the present invention provide a method for acquiring electricity data, applied to a nuclear power plant control system. The nuclear power plant control system includes an electricity acquisition device and an electricity meter. The method includes: acquiring raw electricity data from the electricity meter through the electricity acquisition device; parsing the raw electricity data and generating daily electricity statistics based on a preset algorithm; writing the daily electricity statistics into a management database through a secure transmission mechanism; authorizing each terminal to access the electricity data in the management database via a network based on a web page publishing mechanism; and monitoring the electricity data for anomalies and issuing a warning signal when a preset abnormal condition is detected.

[0006] Secondly, embodiments of the present invention also provide a power data acquisition device for performing the power data acquisition method described above.

[0007] Thirdly, embodiments of the present invention also provide a computer device, the computer device including a memory and a processor connected to the memory; the memory is used to store a computer program; the processor is used to run the computer program stored in the memory to perform the steps of the above-described power data acquisition method.

[0008] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor, can implement the steps of the above-described power data acquisition method.

[0009] Compared with the prior art, the beneficial effects of the present invention are: In the technical solution of this invention, the electricity data acquisition method automatically acquires electricity meter data through an electricity data acquisition device, replacing manual meter reading and improving data accuracy and real-time performance. Daily electricity statistics are generated through parsing and algorithm processing, and written to a management database via a secure transmission mechanism to ensure data integrity and network security. A web-based publishing mechanism allows authorized terminals to remotely view electricity information online within the industrial network, breaking down information silos. Finally, an anomaly monitoring mechanism is introduced to provide real-time warnings for sudden changes in electricity consumption, abnormal transformer losses, and other situations, enabling timely detection of metering circuit faults. This method achieves automated, visualized, and intelligent management and control of the entire electricity data chain, significantly improving the safety and efficiency of nuclear power plant operation. Attached Figure Description

[0010] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0011] Figure 1 A flowchart of the power data acquisition method provided by the present invention; Figure 2 This is a first sub-flowchart of the power data acquisition method provided by the present invention; Figure 3 This is a sub-flowchart of the second sub-flowchart of the power data acquisition method provided by the present invention; Figure 4 The third sub-flowchart of the power data acquisition method provided by the present invention; Figure 5 The fourth sub-flowchart of the power data acquisition method provided by the present invention; Figure 6 The fifth sub-flowchart of the power data acquisition method provided by the present invention; Figure 7 The sixth sub-flowchart of the power data acquisition method provided by the present invention; Figure 8 A schematic block diagram of the unit of the power data acquisition device provided by the present invention; Figure 9 A schematic block diagram of a computer device provided for an embodiment of the present invention. Detailed Implementation

[0012] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0013] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0014] It should also be understood that the terminology used in this specification is for the purpose of describing embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0015] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0016] To address the technical problem that existing power generation data acquisition methods for power plants cannot meet the needs of further intelligent and safe operation, this invention discloses a power generation data acquisition method. This method is applied to a nuclear power plant control system, which includes a high-precision energy meter, such as the Langier FFC3, and a connected energy acquisition device, such as the L0GEW001DP, to achieve automated acquisition and management of nuclear power unit power generation, grid-connected power, and plant power consumption.

[0017] Reference Figures 1 to 7 The power data acquisition method includes the following steps: S110. Obtain raw power data from the power meter through the power acquisition device; S120. The raw power consumption data is parsed, and daily power consumption statistics are generated based on a preset algorithm; S130. Write the daily electricity consumption statistics into the management database through a secure transmission mechanism; S140. Authorize each terminal to access the power data in the management database via the network based on the web page publishing mechanism; S150. Monitor the power data for anomalies and issue a warning signal when a preset abnormal condition is detected.

[0018] The energy acquisition device periodically reads raw energy data from the energy meter via a serial communication interface. This communication uses a non-TCP / IP serial port to achieve physical layer network isolation and prevent reverse data intrusion. Subsequently, the received raw energy data is parsed in the energy workstation, identifying the information of each measuring point. Based on preset transformer ratio parameters, the collected values ​​are converted into actual energy values. Then, based on a daily accumulation algorithm, the daily data is accumulated to generate daily energy statistics including daily power generation, grid-connected power, and plant consumption. Specifically, the "information of each measuring point" refers to the data and status information of each measuring point, such as the meter or sensor, that can be acquired and identified in the monitoring system. Depending on specific needs, this includes location information, identification codes, and measured values.

[0019] Next, through a secure transmission mechanism, including data encryption, one-way transmission channels, firewall whitelist control, and access authentication, the daily electricity consumption statistics are written into a management database, such as the PI real-time database, to ensure the integrity and security of the data during transmission.

[0020] Subsequently, a web publishing service is deployed to bind the electricity data in the management database to a preset daily report webpage template. This generates an electricity display page accessible through a browser, and access is authorized for each terminal. Only authorized terminals located within the same industrial information network segment are allowed to view electricity information by entering a specified IP address, thus ensuring network security and preventing unauthorized access. By restricting access to electricity information to only authorized devices within the same network segment, the potential risks of network attacks and data leaks can be reduced. Simultaneously, the system continuously monitors the electricity data for anomalies. On one hand, it compares the difference between key electricity indicators of the current day and the previous day; if the difference exceeds a preset threshold, a first warning signal is generated to indicate a data mutation. On the other hand, based on power generation, grid-connected electricity, and the electricity consumption of substation A / B, transformer losses are calculated. When the losses are less than zero, a second warning signal is generated, indicating that there may be an anomaly such as increased voltage drop in the electricity meter's metering circuit, achieving early warning of faults.

[0021] In one embodiment, step S110 includes: S111. Continuously monitor the status of the serial communication interface of the power acquisition device; S112. When the serial communication interface is working normally, the power acquisition device reads the original power data in the power meter according to a preset cycle, and temporarily stores the read original power data. S113. When the serial communication interface malfunctions, the local caching mechanism of the power acquisition device is activated to continuously record the original power data that was not successfully uploaded, and the cached data is re-uploaded in timestamp order after communication is restored.

[0022] The energy acquisition device establishes a physical connection with the energy meter via a serial communication interface such as RS-485. The system continuously monitors the connection status and data exchange of this communication interface to determine whether the communication is normal. When the serial communication interface is detected to be working normally, the energy acquisition device automatically reads the raw energy data from the energy meter according to a preset acquisition cycle, including key parameters such as cumulative active power and instantaneous power for each time period, and temporarily stores the read data in the local cache of the energy workstation for subsequent processing. If the system detects abnormalities such as communication interruption, timeout, or verification error, it immediately activates the local cache mechanism built into the energy acquisition device, using its equipped non-volatile storage unit to continuously record the raw energy data that could not be uploaded in real time, and adds a precise timestamp to each data entry. After communication is restored, the system automatically triggers a retransmission process, re-uploading the cached data to the energy workstation in batches according to the timestamp order, ensuring data continuity and integrity. This mechanism effectively copes with temporary communication fluctuations that may occur on-site, avoids data loss due to short-term failures, and improves the reliability of data acquisition.

[0023] In one embodiment, step S120 includes: S121. Load the original power data and apply the ratio parameter to the original collected data to perform unit conversion to obtain the actual power value; S122. Based on the actual electricity value, execute the daily cumulative algorithm to calculate the daily power generation, on-grid electricity, and plant power consumption using daily cycle data; S123. Generate daily electricity statistics based on the daily power generation, on-grid electricity, and plant power consumption, and store them in the management database in a format to be written.

[0024] After the energy acquisition device transmits the collected raw energy data to the energy workstation, the system first loads the raw data and identifies the physical quantities corresponding to each data item according to the pre-configured measurement point information table, such as the cumulative energy on the generation side, the cumulative energy on the grid side, and the energy consumption of transformer A / B. Since the raw data output by the energy meter is usually a pulse quantity or a dimensionless value, further processing is required to convert it into a readable energy value. Therefore, the system calls the pre-set transformation ratio parameters for unit conversion. The transformation ratio parameters include the voltage transformer (PT) ratio, the current transformer (CT) ratio, and the pulse constant set by the energy meter itself, expressed by the formula: Actual charge = Original value × CT ratio × PT ratio / Pulse constant The system calculates the actual electricity consumption in units of "ten thousand kilowatt-hours" or "hundred million kilowatt-hours" to ensure data accuracy meets the statistical requirements for nuclear power plant operation. Subsequently, based on the actual electricity consumption, the system executes a daily cumulative algorithm. This algorithm uses a 24-hour statistical period to extract cumulative electricity consumption data at hourly or 15-minute intervals between 00:00 and 24:00. The incremental values ​​for each time period are calculated using the difference method and then summed to obtain the daily power generation, grid connection power, and plant consumption power. For missing or abnormal data points, the system can use linear interpolation between preceding and following time periods for reasonable compensation, avoiding statistical interruptions due to brief communication delays. Finally, the system integrates the calculated daily power generation, grid connection power, and plant consumption power into structured daily electricity statistics data. This data is then encapsulated according to the data format required by the PI database's management database, including measurement point labels, timestamps, and data quality markers, and stored in the local temporary storage area of ​​the power workstation, awaiting writing to the management database via a secure transmission mechanism.

[0025] To further enhance data reliability, the data quality tagging function has been expanded to include "normal", "suspicious" or "invalid" labels for each data entry during the parsing process. These labels are then used by the subsequent anomaly monitoring module for reference, enabling full-chain traceability and reliable management of the data.

[0026] In one embodiment, step S130 includes: S131. Call the interface of the management database to write the daily electricity statistics data to the specified measurement point; S132. After each write operation is completed, record the operation result to the runtime log file; S133. If the write operation fails, record the exception information in the log and issue an alarm.

[0027] The newly developed data statistics and interface software running on the power consumption workstation initiates the data writing process after generating daily power consumption statistics. Specifically, this newly developed data statistics and interface software refers to a new program or tool developed for collecting, processing, and displaying data. The system first calls the standard application programming interface provided by the management database to establish a secure connection with the database server. During the connection process, it verifies preset authentication information such as the server address, username, and password to ensure that only authorized devices can access the data. After a successful connection, the system writes the packaged daily power consumption statistics item by item into the management database according to measurement point labels, such as "L1_GEN_DAY" and "L1_GRID_IN_DAY", achieving structured data storage and subsequent retrieval.

[0028] To ensure the traceability of data operations, the system records the result of each write operation in the runtime log file, regardless of success or failure. The log content includes information such as write time, data date, involved measurement points, write status, and data volume. When the log file content exceeds a preset number of lines or the program exits normally, the system automatically saves the current log file to the local disk, naming the file with the timestamp of the save time for easy archiving and retrieval. If a write operation fails due to an abnormal situation such as connection interruption, authentication failure, or data format error, the system not only records the abnormality type and occurrence time in detail in the log but also triggers a local alarm. This alarm can be sent to maintenance personnel via sound prompts, pop-up warnings, or alarm signals to the main control monitoring system for timely handling.

[0029] To further improve the reliability of data transmission, an extension mechanism can be added to support breakpoint resume mechanism. After the database service is detected to be restored, the unfinished write task will be automatically retried to ensure the integrity and timeliness of daily power consumption statistics.

[0030] This embodiment combines interface calls, log tracing, and exception response mechanisms to achieve a secure, controllable, and maintainable data writing process, meeting the requirements of nuclear power plants for highly reliable management of critical operational data.

[0031] In one embodiment, step S140 includes: S141. Bind the daily electricity consumption data in the management database to the preset daily report webpage template, and generate a daily electricity consumption report that can be accessed through a browser; S142. Generate an access address that allows access to the daily electricity consumption report via a browser, and configure access permissions for each terminal; S143. When any of the terminals accesses the database, verify whether the terminal is in the same industrial information network segment as the web server of the management database.

[0032] A lightweight web service module is deployed on a dedicated server within the power workstation or industrial information network (KNS network). This module periodically reads the written daily power statistics from the management database via a data interface and binds them to a preset daily report webpage template. This template, built in HTML format, includes a tabular display area to present key indicators such as daily power generation, grid connection power, and plant power consumption. It also supports display by generating unit, forming a clearly structured and easy-to-read daily power report page. The system generates an access address accessible through a common browser, for example, in the form of an IP address plus a port number. Users can view the latest power data by opening a browser and entering this address on any terminal device connected to the KNS network. To ensure access security, the system configures access permissions for each terminal, allowing only authorized operators or roles to access the webpage service. When any terminal initiates an access request, the system first performs network environment verification to determine whether the terminal's IP address is on the same industrial information network segment as the webpage server. If they are not on the same segment, access is denied to prevent unauthorized external devices from accessing the network. This verification mechanism, combined with the physical isolation characteristics of the KNS network, effectively ensures the security of data access. To further enhance the user experience, the system can be expanded to support multi-terminal adaptation, enabling web reports to automatically adapt and display on devices with different resolutions, such as the main control room's large screen and engineer's workstation PCs. An access log recording function can also be added to track the terminal IP, access time, and operational behavior for each access, achieving auditability of the access process.

[0033] This embodiment enables remote viewing of power data with "zero client" capability, requiring no installation of dedicated software. This significantly improves the convenience and intelligence of data acquisition while ensuring safety and controllability, meeting the application requirements of nuclear power plant industrial network environments.

[0034] In one embodiment, step S150 includes: S151. Obtain the data from the daily electricity consumption report of the current day and the previous day, calculate the difference of key electricity consumption indicators, and compare each of the differences with the corresponding preset threshold. S152. If any of the differences exceeds the corresponding preset threshold, a first warning signal is generated to indicate a sudden change in the power data.

[0035] After the daily electricity statistics are generated and written to the management database, the system automatically initiates anomaly monitoring procedures. First, it reads key electricity indicators from the current daily electricity report, including daily power generation, grid connection power, and plant power consumption, and retrieves the corresponding data items from the previous day to form a comparison data set. The system calculates the difference between each key indicator between the two days, such as "daily power generation - previous day's power generation" and "daily grid connection power - previous day's grid connection power," and converts the resulting differences into relative change rates to eliminate the impact of normal differences caused by unit load fluctuations. Subsequently, the system compares each difference or relative change rate with pre-set thresholds. These pre-set thresholds are determined based on statistical analysis of historical operating data of the nuclear power plant; for example, a daily change rate in power generation exceeding ±15% or a grid connection power fluctuation exceeding ±20% is considered abnormal. If any difference exceeds its corresponding pre-set threshold, the system determines it as a sudden change in electricity data and generates a first warning signal. This early warning signal can be presented in multiple ways. Abnormal data items are highlighted in a color such as a flashing red box on the web report interface. An audible alarm or pop-up notification is triggered locally at the power workstation. Simultaneously, the warning information is written to the operation log and can be forwarded to the main control room monitoring system or the operator's duty terminal via the KNS network, ensuring timely notification to relevant personnel. To avoid false alarms caused by brief communication delays or data retransmission, the system can be configured with a delayed judgment mechanism. This means that anomaly comparisons are performed only after 00:30 each day, once the data has fully stabilized, ensuring that the judgment is based on complete and accurate statistical results.

[0036] In addition, the system has been further expanded to include a multi-level threshold mechanism, such as setting two levels of thresholds: "warning" and "serious anomaly," corresponding to different levels of response processes, thereby improving the precision of early warnings.

[0037] Furthermore, the steps in S150 also include: S153. Based on the daily power generation, on-grid power, and plant power consumption, calculate the transformer loss according to the preset loss calculation formula. S154. If the transformer loss is less than zero, a second warning signal is generated to indicate that the electricity meter's metering circuit is abnormal.

[0038] After generating daily electricity statistics, the system further performs logical verification calculations of transformer losses based on the day's power generation, grid connection power, and plant power consumption. Specifically, the system calls the preset loss calculation formula: Transformer losses = Power generation - Power supplied to the grid - Power consumption of transformer A - Power consumption of transformer B Theoretically, the calculation result should be non-negative, reflecting the reasonable losses of the transformer during energy conversion, such as iron loss and copper loss. If the calculation result is less than zero, indicating negative loss, it indicates a logical contradiction in the electricity data, most likely due to an abnormality in the electricity meter's metering circuit. This could be caused by poor contact in the secondary circuit of the voltage transformer leading to increased voltage drop, reversed polarity of the current transformer, or mismatched data due to communication errors. Once the system determines that the transformer loss is less than zero, it automatically generates a second warning signal. This signal is independent of the first warning signal and is specifically used to indicate metering system-level anomalies. The second warning signal can be triggered in various ways, marked with a specific icon in the daily electricity report published on the webpage. A "Metering Circuit Abnormality" prompt is displayed in a pop-up window on the electricity workstation, recording the time of the abnormality, relevant measuring points, and calculated values; simultaneously, the warning information is written to the operation log for subsequent traceability and analysis. To improve the accuracy of the judgment, the system can be set up with a delayed confirmation mechanism to avoid misjudgment of instantaneous negative values ​​due to delayed uploads of individual data points. For example, the calculation can be performed after 00:30 each day, once all data has been completely updated. By introducing logical relationship verification between electricity data, intelligent identification of abnormalities in the electricity meter's metering circuit is achieved, making up for the shortcomings of traditional manual verification in finding hidden faults.

[0039] In addition, the system is also equipped with a historical trend analysis function to monitor the trend of transformer loss values ​​over several consecutive days. If the loss value shows a slow increase or increased fluctuations, even if it does not reach a negative value, a trend warning can be generated to prompt preventive maintenance.

[0040] The power data acquisition method provided by this invention, through the integration of automated acquisition, secure transmission, remote access, and a dual anomaly early warning mechanism, achieves intelligent, networked, and highly reliable operation of nuclear power plant power management. This significantly improves data accuracy and operational efficiency, reduces the burden on operators, and has significant engineering application value. This solution is not only applicable to the current power data optimization management of nuclear power bases such as Daya Bay and Ling'ao, but can also be extended to other nuclear power units and large-scale power plant systems such as thermal and hydropower plants. Especially in the context of promoting the digital transformation of the power system and building smart power plants, it possesses broad applicability and replicability.

[0041] Figure 8 This is a schematic block diagram of a power data acquisition device 600 provided in an embodiment of the present invention. Figure 8 As shown, corresponding to the above-described power data acquisition method, the present invention also provides a power data acquisition device 600. This power data acquisition device 600 includes a unit for performing the above-described power data acquisition method, and the device can be configured in a desktop computer, tablet computer, smartphone, or other terminal.

[0042] Specifically, please refer to Figure 8 The power data acquisition device 600 includes: Data acquisition unit 610 is used to acquire raw power data from the power meter through the power acquisition device; The data parsing unit 620 is used to parse the raw power data and generate daily power statistics based on a preset algorithm; The data acquisition unit 630 is used to write the daily electricity statistics data into the management database through a secure transmission mechanism; The terminal authorization unit 640 is used to authorize each terminal, allowing each terminal to access the power data in the management database via the network based on a web page publishing mechanism; The abnormal warning unit 650 is used to monitor the power data for abnormalities and issue a warning signal when a preset abnormal condition is detected.

[0043] In one embodiment, the data acquisition unit 610 includes: An interface monitoring unit is used to continuously monitor the status of the serial communication interface of the power acquisition device. The normal transmission unit is used to read the original power data from the power meter through the power acquisition device according to a preset cycle when the serial communication interface is working normally, and to temporarily store the read original power data. An abnormal transmission unit is used to activate the local caching mechanism of the power acquisition device when the serial communication interface malfunctions, continuously record the original power data that was not successfully uploaded, and re-transmit the cached data in timestamp order after communication is restored.

[0044] In one embodiment, the data parsing unit 620 includes: The actual power consumption calculation unit is used to load the original power consumption data and apply the ratio parameter to the original collected data to perform unit conversion to obtain the actual power consumption value. The demand data calculation unit is used to execute a daily cumulative algorithm based on the actual electricity value, and calculate the daily power generation, on-grid electricity, and plant power consumption through daily cycle data. The demand data storage unit is used to generate daily electricity statistics based on the daily power generation, on-grid electricity, and plant power consumption, and store them in the management database in a format to be written.

[0045] In one embodiment, the data acquisition unit 630 includes: The data writing unit is used to call the interface of the management database to write the daily electricity statistics data to the specified measuring point; The log recording unit is used to record the operation result to the runtime log file after each write operation is completed; The warning logging unit is used to record exception information and issue an alarm in the log if a write operation fails.

[0046] In one embodiment, the terminal authorization unit 640 includes: The report generation unit is used to bind the daily electricity data in the management database to a preset daily report webpage template and generate a daily electricity report that can be accessed through a browser. The permission issuance unit is used to generate an access address that can be accessed through a browser to access the daily electricity consumption report, and to configure access permissions for each terminal. The security verification unit is used to verify whether the terminal is located in the same industrial information network segment as the web server of the management database when any of the terminals accesses the database.

[0047] In one embodiment, the anomaly warning unit 650 includes: The difference comparison unit is used to obtain data from the daily electricity consumption report of the current day and the previous day, calculate the difference of key electricity consumption indicators, and compare each difference with the corresponding preset threshold. The first warning unit is used to generate a first warning signal if any of the differences exceeds the corresponding preset threshold, indicating a sudden change in the power data.

[0048] Furthermore, the anomaly warning unit 650 also includes: The loss calculation unit is used to calculate the transformer loss based on the daily power generation, on-grid power, and plant power consumption according to a preset loss calculation formula. The second early warning unit is used to generate a second early warning signal if the transformer loss is less than zero, indicating an abnormality in the electricity meter's metering circuit.

[0049] The aforementioned power data acquisition device 600 can be implemented as a computer program, which can, for example... Figure 9 It runs on the computer device shown.

[0050] Please see Figure 9 , Figure 9 This is a schematic block diagram of a computer device 500 provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a desktop computer, tablet computer, or smartphone. The server can be a standalone server or a server cluster composed of multiple servers.

[0051] See Figure 9 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0052] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a power data acquisition method.

[0053] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0054] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a power data acquisition method.

[0055] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 9 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0056] The processor 502 is used to run a computer program 5032 stored in a memory to implement the steps of the above method.

[0057] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0058] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0059] Therefore, the present invention also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the steps of the above-described method.

[0060] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0061] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0062] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0063] The steps in the method of this invention can be adjusted, merged, or reduced in order according to actual needs. The units in the device of this invention can be merged, divided, or reduced according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0064] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention.

[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method of collecting electric power data, characterized by, The application is applied to a nuclear power plant control system, which comprises an electric energy collection device and an electric energy meter, and the method comprises the following steps: acquiring original electric quantity data from the electric energy meter through the electric energy collection device; analyzing the original electric quantity data and generating daily electric quantity statistical data based on a preset algorithm; writing the daily electric quantity statistical data into a management database through a secure transmission mechanism; authorizing each terminal to allow each terminal to access the electric quantity data in the management database through a webpage publishing mechanism based on a network; monitoring the electric quantity data for abnormalities and issuing a warning signal when a preset abnormal condition is detected.

2. The method of claim 1, wherein, The step of acquiring original electric quantity data from the electric energy meter through the electric energy collection device comprises the following steps: continuously monitoring the state of the serial communication interface of the electric energy collection device; when the serial communication interface is working normally, reading the original electric quantity data in the electric energy meter through the electric energy collection device according to a preset period, and temporarily storing the read original electric quantity data; when the serial communication interface is working abnormally, starting the local cache mechanism of the electric energy collection device, continuously recording the original electric quantity data that is not successfully uploaded, and after the communication is restored, supplementing the cache data in time stamp order.

3. The method of claim 1, wherein the electric quantity data is collected by a plurality of sensors. The step of analyzing the original electric quantity data and generating daily electric quantity statistical data based on a preset algorithm comprises the following steps: loading the original electric quantity data, applying a variable ratio parameter to the original collection data to perform unit conversion, and obtaining an actual electric quantity value; based on the actual electric quantity value, executing a daily cumulative calculation algorithm to calculate the daily power generation, grid-connected power and plant power through 24-hour period data; based on the daily power generation, grid-connected power and plant power, generating daily electric quantity statistical data and storing it in a management database in a to-be-written format.

4. The method of claim 3, wherein the step of collecting the electric quantity data is performed by a plurality of electric quantity data collecting devices. The step of writing the daily electric quantity statistical data into a management database through a secure transmission mechanism comprises the following steps: calling the interface of the management database to write the daily electric quantity statistical data into a specified measurement point; after each writing operation is completed, recording the operation result in a running log file; if the writing operation fails, recording abnormal information in the log and prompting an alarm.

5. The method of claim 4, wherein the step of collecting the electric quantity data is performed by a plurality of electric quantity data collecting devices. The step of authorizing each terminal to allow each terminal to access the electric quantity data in the management database through a webpage publishing mechanism based on a network comprises the following steps: binding the daily electric quantity data in the management database to a preset daily report webpage template, and generating a daily electric quantity report that can be accessed through a browser; generating an access address of the daily electric quantity report that can be accessed through a browser, and configuring access permissions for each terminal; when any of the terminals accesses, verifying whether the terminal is in the same network segment of the industrial information network as the webpage server of the management database.

6. The electric quantity data collecting method according to claim 5, wherein The step of monitoring the electric quantity data for abnormalities and issuing a warning signal when a preset abnormal condition is detected comprises the following steps: acquiring the data in the daily electric quantity report of the current day and the previous day, calculating the difference of the key electric quantity indicators, and comparing the differences with the corresponding preset threshold values; if any of the differences exceeds the corresponding preset threshold value, a first warning signal is generated to prompt an electric quantity data mutation.

7. The electric quantity data collecting method according to claim 6, wherein The step of performing abnormal monitoring on the electric quantity data and sending a pre-warning signal when a preset abnormal condition is detected further includes: calculating transformer loss according to a preset loss calculation formula based on the daily power generation, on-grid power, and plant power consumption; if the transformer loss is less than zero, generating a second pre-warning signal to prompt an electric energy metering loop abnormality.

8. An electric power data collection device, characterized by comprising: A device for performing the electric quantity data acquisition method as claimed in any one of claims 1 to 7.

9. A computer device, comprising: The computer device includes a memory and a processor connected to the memory; the memory is used to store a computer program; and the processor is used to run the computer program stored in the memory to perform the steps of the method as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program includes program instructions which, when executed by a processor, can implement the steps of the method as claimed in any one of claims 1 to 7.

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