Generator set water vapor instrument three-level control and benchmarking management method and system

Abstract

The invention discloses a three-level management and control and benchmarking management method and system for a water vapor instrument of a generator set. The method comprises the following steps: collecting basic-level power plant-level data, regional company-level data and group headquarter-level data; constructing a basic-level power plant level billboard according to the basic-level power plant level data; constructing a regional company level billboard according to the regional company level data; constructing a group headquarter-level billboard according to the group headquarter-level data; constructing a benchmarking system; performing benchmarking and optimization of each basic-level power plant based on the basic-level power plant data and a benchmarking system; based on the regional company level data and the benchmarking system, benchmarking and optimization of each regional company are carried out. The method and the system are suitable for collaborative management and control and benchmarking optimization of water vapor instruments of group level, regional level and grassroots power plant level.

Description

Technical Field

[0001] This invention belongs to the field of power plant instrumentation control technology, and relates to a three-level control and benchmarking management method and system for generator set water and steam instruments. Background Technology

[0002] The current management system for water and steam instruments in thermal power units suffers from severe hierarchical fragmentation. Data collaboration and efficient management are impossible between the group, regional, and grassroots power plant levels. Grassroots power plants can only record instrument data (such as daily extreme values ​​and number of malfunctions) in Excel spreadsheets, manually summarizing it to the regional company by the 5th of each month. The regional company then reorganizes the data from each grassroots unit (e.g., standardizing the statistical format) and reports it to the group headquarters by the 10th of each month—the entire data aggregation process takes over a week, and data accuracy relies on manual verification (in one quarter, a regional company's instrument normality rate deviated by 3% due to three grassroots power plants failing to report data). Furthermore, there is a lack of real-time data sharing channels between the three levels. The group headquarters cannot monitor the instrument status of grassroots power plants in real time. During one group inspection, it was discovered that a silicon content instrument at a grassroots power plant had malfunctioned and shut down for two days, but neither the regional company nor the group was aware of this in time, leading to the power plant operating with substandard water and steam quality, affecting unit safety.

[0003] The lack of a benchmarking management system further leads to uneven operation and maintenance levels: Currently, the effectiveness of instrument operation and maintenance in grassroots power plants can only be evaluated through "experience-based judgment," lacking scientific benchmarking indicators and analytical methods. For example, power plant A's instrument fault repair time is 4 hours, while power plant B's is 12 hours. However, due to the lack of a unified standard for calculating "fault repair time" (power plant A counts from the occurrence of the fault to the completion of the repair, while power plant B counts from the creation of the work order), it is impossible to objectively compare the operation and maintenance efficiency of the two. Furthermore, a benchmarking dimension of "instrument status - unit adaptation" has not been established. For instance, the support rate of instrument data for unit deep adjustment (the number of times deep adjustment parameters are adjusted based on instrument data / the total number of deep adjustments) of a certain power plant reaches 90%, while that of another power plant is only 60%. However, due to the lack of benchmarking analysis, the power plant with the low support rate cannot identify its own shortcomings and continues to use the old operation and maintenance model, resulting in a 1g / kWh increase in coal consumption during unit deep adjustment compared to the power plant with the high support rate.

[0004] The lack of visualization and control capabilities exacerbates decision-making delays: Instrument monitoring at grassroots power plants often uses local 2D interfaces, displaying only data from their own plant; regional companies need to open multiple Excel spreadsheets to compare data from various power plants. For example, to view the "ranking of instrument uptime rates for power plants within the region," they must manually calculate the uptime rate (number of uptime instruments / total number of instruments) for 10 power plants, then sort and organize the data, taking 1.5 hours; the group headquarters lacks an overall visualization interface, only able to understand the overall instrument status of power plants nationwide through static reports, unable to intuitively identify "regional disparities" (e.g., 95% uptime rate in the eastern region, 88% in the western region), resulting in a lack of data support for group-level operation and maintenance resource allocation (e.g., spare parts coordination, technical support)—once, a power plant in the western region urgently needed silicon content instrument sensors, but the group failed to promptly grasp the spare parts reserves in that region, and it took 3 days to transport spare parts from the east, delaying fault handling.

[0005] Furthermore, the lack of benchmarking for unit adaptability also leads to instrument data failing to effectively support the needs of the new power system: Currently, there are no benchmarking indicators such as "impact rate of instrument failure on unit deep dispatch capability" (number of times the unit could not perform deep dispatch due to instrument failure / total number of deep dispatches). One power plant was fined for failing to execute deep dispatch instructions from the grid dispatching system multiple times due to this impact rate being as high as 8% (the industry average is 3%). However, because it did not benchmark against other power plants, the root cause of the problem could not be found (subsequent investigation revealed that the power plant's instrument calibration cycle was too long, resulting in inaccurate measurement data). Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the prior art and provide a three-level control and benchmarking management method and system for water and steam instruments in generator sets. This method and system are applicable to the collaborative control and benchmarking optimization of water and steam instruments at the group level, regional level, and grassroots power plant level.

[0007] To achieve the above objectives, this invention discloses a three-level control and benchmarking management method for water and steam instruments in generator sets, comprising: Collect data at the grassroots power plant level, regional company level, and group headquarters level; Build dashboards at the grassroots power plant level based on grassroots power plant level data; build dashboards at the regional company level based on regional company level data; build dashboards at the group headquarters level based on group headquarters level data. Build a benchmarking system; Benchmarking and optimization of each grassroots power plant are carried out based on the aforementioned grassroots power plant-level data and benchmarking system; benchmarking and optimization of each regional company are carried out based on the aforementioned regional company-level data and benchmarking system.

[0008] Furthermore, the grassroots power plant-level data includes measurement data, status data, and operation and maintenance data of the grassroots power plant.

[0009] Furthermore, the process of collecting regional company-level data is as follows: Obtain grassroots power plant-level data from each grassroots power plant under the regional company, and clean and summarize the obtained data.

[0010] Furthermore, the process of collecting data at the group headquarters level is as follows: Acquire regional company-level data from all regional companies under the group headquarters, and construct a four-level data index of group-region-grassroots-inspection, while verifying the integrity of the data at preset intervals.

[0011] Furthermore, the indicators in the benchmarking system include status benchmarking indicators, data benchmarking indicators, and unit adaptation benchmarking indicators.

[0012] Furthermore, the status benchmarking indicators include instrument normal operation rate, fault repair time, and calibration cycle compliance rate; The data benchmarking indicators include measurement data accuracy and data completeness. The unit adaptation benchmarks include the impact rate of instrument failures on the unit's deep adjustment capability and the support rate of instrument data for the unit's rapid start-up and shutdown.

[0013] This invention discloses a three-level control and benchmarking management system for generator set water and steam instruments, comprising: The data acquisition module is used to collect data at the grassroots power plant level, regional company level, and group headquarters level. The first construction module is used to build a grassroots power plant-level dashboard based on grassroots power plant-level data; to build a regional company-level dashboard based on regional company-level data; and to build a group headquarters-level dashboard based on group headquarters-level data. The second building module is used to construct the benchmarking system; The optimization module is used to benchmark and optimize each grassroots power plant based on the grassroots power plant-level data and benchmarking system; and to benchmark and optimize each regional company based on the regional company-level data and benchmarking system.

[0014] Furthermore, the indicators in the benchmarking system include status benchmarking indicators, data benchmarking indicators, and unit adaptation benchmarking indicators; The status benchmarking indicators include instrument normality rate, fault repair time, and calibration cycle compliance rate. The data benchmarking indicators include measurement data accuracy and data completeness. The unit adaptation benchmarks include the impact rate of instrument failures on the unit's deep adjustment capability and the support rate of instrument data for the unit's rapid start-up and shutdown.

[0015] This invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the generator set water and steam instrument three-level control and benchmarking management method.

[0016] This invention discloses a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the generator set water and steam instrument three-level control and benchmarking management method.

[0017] The present invention has the following beneficial effects: The generator set water and steam instrument three-level control and benchmarking management method and system described in this invention, in specific operation, constructs a grassroots power plant-level dashboard based on grassroots power plant-level data; constructs a regional company-level dashboard based on regional company-level data; constructs a group headquarters-level dashboard based on group headquarters-level data; constructs a benchmarking system; performs benchmarking and optimization of each grassroots power plant based on the grassroots power plant-level data and benchmarking system; and performs benchmarking and optimization of each regional company based on the regional company-level data and benchmarking system. It is applicable to the collaborative control and benchmarking optimization of water and steam instruments at the group level, regional level, and grassroots power plant level. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0020] 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.

[0021] In the description of this invention, it should be understood that 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.

[0022] It should also be understood that the terminology used in this specification is for the purpose of describing particular 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.

[0023] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this invention generally indicates that the preceding and following objects have an "or" relationship.

[0024] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0025] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0027] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0028] Example 1 The generator set water and steam instrument three-level control and benchmarking management method of the present invention includes the following steps: 1) Three-level data acquisition and transmission steps: Construct a three-tiered data transmission architecture at the grassroots, regional, and group levels to achieve real-time collection and secure transmission of all data: Data acquisition at the grassroots power plant level: Deploy local data acquisition terminals (hardware configuration: CPU Intel Core i5, memory 8GB, hard drive 500GB SSD, operating system Windows Server 2019), and collect data through the following methods: Measurement data: pH value, hydrogen conductivity value, silicon content, etc. are collected from the OPC UA interface of the SIS system at a frequency of 1 time / minute, and the data accuracy is retained to 2 decimal places; Status data: The instrument controller's Modbus-TCP interface is used to collect operating status (0-normal, 1-warning, 2-fault), fault repair time (fault occurrence time - repair completion time), and calibration records (calibration time, calibration deviation). The data is collected once every 5 minutes. Operation and maintenance data: Spare parts replacement records (spare parts model, replacement time), inspection records (inspection personnel, problems found), and unit adaptation data (number of times instrument failures prevented in-depth adjustments, number of times start-up and shutdown parameters were adjusted based on instrument data) are collected from the grassroots power plant operation and maintenance management system in real time (recorded immediately when they occur). The collected data is stored in a local database (MySQL, using master-slave backup) in the format of "instrument ID-data type-timestamp" and uploaded to the regional company via a dedicated VPN (Virtual Private Network, encrypted IPsec protocol). The upload frequency is: real-time data once per minute, and summary data (such as daily statistics) once per day.

[0029] Regional company-level data processing and transmission: Deploy a regional data center (server configuration: CPU Intel Xeon E5, memory 32GB, hard disk 2TB SSD, database uses PostgreSQL cluster), and after receiving data uploaded by each grassroots power plant, perform the following processing: Data cleaning: Remove invalid data (such as measured values ​​exceeding the instrument range, timestamp deviation > 10 seconds), and complete missing data (using linear interpolation, missing duration < 30 minutes). Data aggregation: Data within the region is aggregated by "day / week / month" (e.g., daily aggregation of instrument uptime and average fault repair time for each power plant); the processed data is stored in the regional database (retained for 1 year) and uploaded to the group headquarters via the group's dedicated fiber optic cable (1000Mbps bandwidth). Upload frequency: real-time data once every 5 minutes, aggregated data once a day. Data is encrypted with SSL 3.0 before transmission to ensure data security.

[0030] Group headquarters-level data storage and management: Deploy a group-level data platform (using a Hadoop distributed architecture, with a storage capacity of 100TB and support for horizontal scaling), receive data uploaded by regional companies, and build a four-level data index of "group-region-grassroots-instrument," supporting quick queries by "region, power plant, instrument type, and time range." At the same time, establish a data quality monitoring mechanism to automatically verify data integrity (data upload rate of each grassroots power plant ≥99%) and accuracy (deviation between measurement data and laboratory test values ​​≤5%) daily, and trigger early warnings for substandard data (pushed to regional company data administrators).

[0031] 2) Construct a three-level unified data dashboard; A data dashboard titled "One-Stop View of Water Vapor Instrumentation" was built using WebGL technology to achieve visualization and data drill-down for three-level control. Basic power plant-level dashboards: Display dimensions include: Instrument Distribution Visualization: Using the power plant site plan as a background, the installation locations of all water and steam instruments are marked at a 1:1 scale (e.g., the condenser outlet of Unit #1, the economizer inlet of Unit #2). Instrument status is indicated by color (green - normal, yellow - warning, red - fault). Clicking on the instrument icon will bring up the "Instrument Details Window" (including the measurement trend chart of the past 24 hours, status change records, remaining lifespan, and number of unresolved faults). Key data statistics: Displays core indicators such as "Daily instrument normality rate", "Average fault repair time", and "Number of exceedances". When an indicator is abnormal (such as normality rate <95%), it will flash to remind you. Task Management: Displays pending maintenance work orders (including work order ID, instrument ID, fault type, and deadline), and supports work order retrieval and status updates.

[0032] Regional company-level dashboards: Display dimensions include: Overall regional status: Displays the "Total number of instruments", "Number of normal instruments", "Number of warning instruments", and "Number of fault instruments" within the region. It also calculates the region's instrument uptime rate (number of normal instruments / total number of instruments) and displays it using dashboard charts. Benchmarking of grassroots power plants: The bar chart displays the comparison of core indicators of each grassroots power plant (such as instrument uptime, fault repair time, and data integrity rate), and supports sorting by indicator (such as sorting by uptime from high to low). Anomaly Focus: Highlights power plants with "more than 3 faulty instruments" or "normal rate <90%". Clicking on the power plant name will drill down to the power plant's basic dashboard. Trend Analysis: Displays the weekly / monthly trends of core indicators within the region (such as changes in instrument normality rate over the past 4 weeks), and supports prediction of trends for the next week (based on a linear regression algorithm).

[0033] Group headquarters-level dashboard: Display dimensions include: Group Overview: With a map of China as the background, the locations of regional companies are marked, and the regional instrument uptime is indicated by color (red <90%, yellow 90%-95%, green >95%). Hovering the mouse over the area displays "Total Number of Instruments", "Number of Faults", and "Mean Time to Repair". Regional Benchmarking Ranking: The benchmarking results of each regional company are displayed in a table or radar chart (including status benchmarking, data benchmarking, and unit adaptation benchmarking scores). The score is calculated as follows: (actual value of each indicator / industry excellent value) × weight (status benchmarking weight 40%, data benchmarking weight 30%, unit adaptation weight 30%). Key monitoring: List areas with "fault repair time > 8 hours" and "unit compatibility impact rate > 5%". Click on an area to drill down to the area dashboard, and then drill down to the base dashboard. Resource scheduling: Displays the spare parts reserve status of each region (such as the number of sensors in stock and the number available for allocation), and supports the issuance of group-level spare parts scheduling instructions (such as transferring 5 silicon content sensors from the eastern region to the western region).

[0034] 3) Establish a benchmarking system: Construct a three-dimensional benchmarking indicator system of "status-data-unit adaptation", and clarify the definition, calculation method and evaluation criteria of each indicator: Status benchmarking indicators: Instrument normal operation rate: defined as "total duration of instruments operating normally within the statistical period / (total number of instruments × duration of the statistical period) × 100%", where the statistical period is divided into daily (24 hours), monthly (30 days), and quarterly (90 days); evaluation criteria: excellent > 98%, good 95%-98%, qualified 90%-95%, unqualified < 90%; Fault repair time: defined as "the sum of (repair completion time - fault occurrence time) of all faults within the statistical period / total number of faults". The fault occurrence time is based on the instrument triggering the fault signal, and the repair completion time is based on the maintenance personnel marking "completed" on the platform; evaluation criteria: excellent < 4 hours, good 4-6 hours, qualified 6-8 hours, unqualified > 8 hours; Calibration cycle compliance rate: defined as "the number of instruments that have completed calibration according to the standard calibration cycle within the statistical period / the total number of instruments × 100%". The standard calibration cycle is set according to the instrument type (pH instrument 7 days, hydrogen conductivity instrument 14 days, silicon content instrument 30 days); evaluation criteria: excellent > 98%, good 95%-98%, qualified 90%-95%, unqualified < 90%.

[0035] Data benchmarking indicators: Measurement data accuracy: defined as "the number of times the measured value deviates from the laboratory test value by ≤5% within the statistical period / the total number of tests × 100%", with laboratory tests conducted once daily and compared synchronously with instrument measurements; evaluation criteria: Excellent >97%, Good 95%-97%, Pass 92%-95%, Unpass <92%; Data completeness rate: defined as "the amount of valid data collected within the statistical period / the amount of data that should be collected × 100%", where valid data refers to data with a quality label of "0-valid" and the amount of data that should be collected = the total number of instruments × the statistical period × the collection frequency; evaluation criteria: excellent > 99%, good 98%-99%, qualified 95%-98%, unqualified < 95%.

[0036] Unit adaptation benchmarks: Impact rate of instrument failure on unit deep dispatch capability: defined as "the number of times the unit could not execute deep dispatch commands due to instrument failure within the statistical period / the total number of deep dispatch commands × 100%", where deep dispatch commands refer to dispatch commands that reduce the load to below 50% of the rated load; evaluation criteria: excellent <2%, good 2%-5%, qualified 5%-8%, unqualified >8%; The support rate of instrument data for rapid start-up and shutdown of the unit is defined as "the number of unit start-ups and shutdowns based on instrument data adjustment parameters within the statistical period / the total number of start-ups and shutdowns × 100%", where the adjustment parameters include start-up and shutdown rate and water quality conditioner addition amount; evaluation criteria: excellent > 90%, good 80%-90%, qualified 70%-80%, unqualified < 70%.

[0037] 4) Benchmarking analysis and optimization steps: Establish a closed-loop benchmarking management process: "regular benchmarking - difference analysis - optimization and improvement - results promotion". Regular benchmarking: Monthly benchmarking: Before the 5th of each month, grassroots power plants shall complete the internal benchmarking of the previous month (such as the benchmarking of instruments in each workshop), generate the "Monthly Benchmarking Report of Grassroots Power Plants", and submit it to the regional company; the regional company shall complete the benchmarking of grassroots power plants in the region before the 10th of each month, generate the "Regional Monthly Benchmarking Report" (including the ranking of each power plant and the analysis of differences), and submit it to the group headquarters; Quarterly benchmarking: Before the 15th of the first month of each quarter, the group headquarters completes the benchmarking of all regional companies across the country, generates the "Group Quarterly Benchmarking Report", and holds a benchmarking meeting (offline + online) to announce the benchmarking results and commend outstanding regions / power plants.

[0038] Difference analysis: Indicator Difference Identification: For units with lower rankings (such as power plants with the lowest normal operation rate in the region), analyze the reasons for the differences in benchmark indicators one by one. For example, if a power plant has a long fault repair time (10 hours), data tracing reveals that: there is insufficient spare parts reserve (only 2 sensors are in stock, which is lower than the standard of "1 spare part for every 5 instruments") and insufficient skills of maintenance personnel (only 1 out of 3 maintenance personnel is proficient in repairing imported instruments). Root cause analysis: Using the "fishbone diagram" analysis method, we dig out the root causes from five dimensions: "people, machines, materials, methods, and environment"—for example, the root cause of insufficient spare parts is "the cumbersome spare parts procurement process in grassroots power plants (requiring 5 approval steps and taking 7 days)", rather than simply "insufficient budget".

[0039] Optimization and Improvement: Develop solutions: Develop targeted optimization solutions based on the root causes of the differences—for example, insufficient spare parts: regional companies establish a "regional spare parts sharing warehouse" (stocking commonly used spare parts, such as sensors and electrodes), and simplify the procurement process of grassroots power plants to "3 approval steps, with a time of ≤3 days"; insufficient operation and maintenance skills: the group organizes "imported instrument repair training courses" once a month, and those who pass the assessment are allowed to work. Tracking Implementation: The optimized plan clearly defines the "responsible department, completion deadline, and acceptance criteria." For example, the regional spare parts sharing warehouse needs to be built within 2 months, and the acceptance criteria are "common spare parts coverage rate ≥90% and dispatch time <24 hours." The regional company tracks the progress of the plan weekly and triggers an early warning when the standards are not met.

[0040] Promotion of Results: Experience distillation: Summarize the operation and maintenance experience of outstanding units (such as the operation and maintenance model of a power plant that combines "instrument inspection + remote diagnosis", which has increased the normal operation rate to 99%), and form standardized cases (including implementation steps, resource requirements, and effect data). Group Promotion: Promote best practices through the group's intranet, training meetings, on-site visits, etc., such as organizing regional companies to learn from excellent power plants or recording operation videos and uploading them to the group's training platform; at the same time, incorporate mature experience into the "Group Water and Steam Instrument Operation and Maintenance Standards" and enforce their implementation (such as incorporating "calibrating pH instruments every 7 days" into the standards).

[0041] Example 2 Taking a certain region of Huaneng Group (including 5 grassroots power plants, each equipped with 20-30 water and steam instruments) as an example, the implementation process is as follows: Level 3 data collection: Grassroots power plants: Collect instrument status (e.g., 23 out of 25 instruments in #1 power plant are normal, and 2 are in warning mode), measurement data (e.g., average silicon content of 15μg / L), and operation and maintenance data (average fault repair time of 8 hours), and upload them to the regional company via an SSL encrypted network; Regional Company: Compile data from 5 grassroots power plants (regional instrument normality rate 92%) and upload it to the group headquarters; Group Headquarters: Receives data from 10 regions across the country and establishes a group database; Data dashboard construction: Grassroots dashboard: 3D display of the distribution of instruments in power plant #1, with 2 early warning instruments marked in red (sensor aging), showing the trend of silicon content measurement data; Regional dashboard: Displays the ranking of instrument uptime of 5 power plants (#3 power plant 98% first, #5 power plant 85% last), and you can drill down to view specific faulty instruments in #5 power plant; Group dashboard: Displays the ranking of instrument normalization rate in 10 regions (6th in this region), and indicates the difference between this region and the first place (6%). Application of benchmarking system: Status benchmark: The repair time for the fault at power plant #5 is 12 hours (8 hours for the region), because spare parts need to be transferred from the regional warehouse, which takes 4 hours. Data benchmarking: The accuracy of measurement data at power plant #2 was 88% (regional average 95%), due to the excessively long calibration cycle (3 months / time, compared to the standard of 1 month / time). Unit adaptation standards: #4 Power plant instrument failures have a 5% impact rate on deep adjustment (regional average 2%), due to frequent failures of silicon content instruments; Optimization and Improvement: For Power Plant #5: A spare parts warehouse was set up at Power Plant #5 in the region, reducing the fault repair time to 6 hours; For Power Plant #2: The calibration cycle was mandated to be adjusted to one month, and the data accuracy rate was improved to 94%. For Power Plant #4: Promote the experience of "monthly inspection of silicon content instruments" from Power Plant #3, and solve the problem of frequent failures; Quarterly benchmarking: The instrument uptime rate in this region has increased to 96%, and the group ranking has risen to 3rd.

[0042] In summary, this invention addresses the disconnect and lack of benchmarking in the three-tiered management and control of water and steam instrumentation at the group, regional, and grassroots levels by constructing a collaborative management and benchmarking system. Technically, it establishes a three-tiered data link of "grassroots data collection - regional processing - group storage," collecting instrument measurement, status, operation and maintenance, and unit adaptation data, ensuring security through encrypted transmission. It constructs a unified three-tiered data dashboard to achieve instrument status visualization and data drill-down. It establishes a three-dimensional benchmarking system of "status (normality rate, fault repair time) - data (accuracy rate, completeness rate) - unit adaptation (deep-shift impact rate, start-up and shutdown support rate)," conducting regular monthly / quarterly benchmarking to analyze the root causes of discrepancies and develop optimization solutions (such as regional spare parts sharing and skills training), and promoting best practices. The core value lies in achieving three-tiered collaborative management and control, scientifically identifying operational and maintenance shortcomings through benchmarking, improving the efficiency of group-level water and steam instrumentation management and control, and supporting the safe operation of units and the deep peak-shaving needs under the new power system.

[0043] Example 3 The generator set water and steam instrument three-level control and benchmarking management system of the present invention includes: The data acquisition module is used to collect data at the grassroots power plant level, regional company level, and group headquarters level. The first construction module is used to build a grassroots power plant-level dashboard based on grassroots power plant-level data; to build a regional company-level dashboard based on regional company-level data; and to build a group headquarters-level dashboard based on group headquarters-level data. The second building module is used to construct the benchmarking system; The optimization module is used to benchmark and optimize each grassroots power plant based on the grassroots power plant-level data and benchmarking system; and to benchmark and optimize each regional company based on the regional company-level data and benchmarking system.

[0044] Furthermore, the indicators in the benchmarking system include status benchmarking indicators, data benchmarking indicators, and unit adaptation benchmarking indicators; The status benchmarking indicators include instrument normality rate, fault repair time, and calibration cycle compliance rate. The data benchmarking indicators include measurement data accuracy and data completeness. The unit adaptation benchmarks include the impact rate of instrument failures on the unit's deep adjustment capability and the support rate of instrument data for the unit's rapid start-up and shutdown.

[0045] The module division in this embodiment is illustrative and represents only one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional modules in each embodiment of this application can be integrated into a single processor, exist as separate physical entities, or be integrated into a single module. The integrated modules described above can be implemented in hardware or as software functional modules.

[0046] Example 4 A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of a three-level control and benchmarking management method for generator set water and steam instruments. For example, the steps include: collecting data at the grassroots power plant level, regional company level, and group headquarters level; constructing a grassroots power plant-level dashboard based on the grassroots power plant-level data; constructing a regional company-level dashboard based on the regional company-level data; constructing a group headquarters-level dashboard based on the group headquarters-level data; constructing a benchmarking system; benchmarking and optimizing each grassroots power plant based on the grassroots power plant-level data and the benchmarking system; and benchmarking and optimizing each regional company based on the regional company-level data and the benchmarking system. The memory may include main memory, such as high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device. The processor, network interface, and memory are interconnected via an internal bus, which can be an industry standard architecture bus, a peripheral component interconnection standard bus, an extended industry standard architecture bus, etc. The bus can be divided into address bus, data bus, control bus, etc. The memory is used to store programs; specifically, the program may include program code, which includes computer operation instructions. The memory may include main memory and non-volatile memory, and provides instructions and data to the processor.

[0047] Example 5 A computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of a three-level control and benchmarking management method for generator set water and steam instruments. For example, the steps include: collecting data at the grassroots power plant level, regional company level, and group headquarters level; constructing a grassroots power plant-level dashboard based on the grassroots power plant-level data; constructing a regional company-level dashboard based on the regional company-level data; constructing a group headquarters-level dashboard based on the group headquarters-level data; constructing a benchmarking system; benchmarking and optimizing each grassroots power plant based on the grassroots power plant-level data and the benchmarking system; and benchmarking and optimizing each regional company based on the regional company-level data and the benchmarking system. Specifically, the computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. The volatile memory may include random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include read-only memory (ROM), hard disk, flash memory, optical disk, magnetic disk, etc.

[0048] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0049] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0050] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0051] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0052] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and disclosure of the invention. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the following claims.

[0053] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

[0054] The above description is merely a preferred embodiment of the present invention and does not constitute any limitation on the present invention. Any simple modifications, alterations, or equivalent structural changes made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A three-level control and benchmarking management method for water and steam instruments in generator sets, characterized in that, include: Collect data at the grassroots power plant level, regional company level, and group headquarters level; Construct a grassroots power plant-level dashboard based on grassroots power plant-level data; Build regional company-level dashboards based on regional company-level data; build group headquarters-level dashboards based on group headquarters-level data; Build a benchmarking system; Benchmarking and optimization of each grassroots power plant are carried out based on the aforementioned grassroots power plant-level data and benchmarking system; benchmarking and optimization of each regional company are carried out based on the aforementioned regional company-level data and benchmarking system.

2. The three-level control and benchmarking management method for generator set water and steam instruments according to claim 1, characterized in that, The grassroots power plant-level data includes measurement data, status data, and operation and maintenance data of the grassroots power plant.

3. The three-level control and benchmarking management method for generator set water and steam instruments according to claim 1, characterized in that, The process of collecting regional company-level data is as follows: Obtain grassroots power plant-level data from each grassroots power plant under the regional company, and clean and summarize the obtained data.

4. The three-level control and benchmarking management method for generator set water and steam instruments according to claim 1, characterized in that, The process of collecting data at the group headquarters level is as follows: Acquire regional company-level data from all regional companies under the group headquarters, and construct a four-level data index of group-region-grassroots-inspection, while verifying the integrity of the data at preset intervals.

5. The three-level control and benchmarking management method for generator set water and steam instruments according to claim 1, characterized in that, The benchmarking system includes indicators for status benchmarking, data benchmarking, and unit adaptation benchmarking.

6. The three-level control and benchmarking management method for generator set water and steam instruments according to claim 5, characterized in that, The status benchmarking indicators include instrument normality rate, fault repair time, and calibration cycle compliance rate. The data benchmarking indicators include measurement data accuracy and data completeness. The unit adaptation benchmarks include the impact rate of instrument failures on the unit's deep adjustment capability and the support rate of instrument data for the unit's rapid start-up and shutdown.

7. A three-level control and benchmarking management system for generator set water and steam instruments, characterized in that, include: The data acquisition module is used to collect data at the grassroots power plant level, regional company level, and group headquarters level. The first construction module is used to build a grassroots power plant-level dashboard based on grassroots power plant-level data; to build a regional company-level dashboard based on regional company-level data; and to build a group headquarters-level dashboard based on group headquarters-level data. The second building module is used to build the benchmarking system; The optimization module is used to benchmark and optimize each grassroots power plant based on the grassroots power plant-level data and benchmarking system; and to benchmark and optimize each regional company based on the regional company-level data and benchmarking system.

8. The generator set water and steam instrument three-level control and benchmarking management system according to claim 7, characterized in that, The benchmarking system includes indicators for status benchmarking, data benchmarking, and unit adaptation benchmarking. The status benchmarking indicators include instrument normality rate, fault repair time, and calibration cycle compliance rate. The data benchmarking indicators include measurement data accuracy and data completeness. The unit adaptation benchmarks include the impact rate of instrument failures on the unit's deep adjustment capability and the support rate of instrument data for the unit's rapid start-up and shutdown.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the generator set water and steam instrument three-level control and benchmarking management method as described in any one of claims 1-6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the generator set water and steam instrument three-level control and benchmarking management method as described in any one of claims 1-6.

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