Pumped storage power station operation analysis and evaluation method and system based on multi-source data

Abstract

The invention relates to the field of data processing, and discloses a pumped storage power station operation analysis and evaluation method and system based on multi-source data, and the method comprises the steps: collecting the multi-source data, carrying out the statistics and classified storage of the collected multi-source data, and carrying out the statistics of the multi-source data according to the demands of a data analysis process; classifying and storing the multi-source data according to a statistical result; screening out feature data from the monitoring data according to user requirements, and generating a visual analysis graph; and forming an analysis report according to the visual analysis graph and the classified multi-source data. The system can perform statistical analysis on important information such as operation indexes, unit trend, power transmission and transformation equipment state analysis and equipment action times of the pumped storage power station, displays, analyzes and evaluates the equipment state information, and further provides a guidance scheme for operation of the power station so as to realize high-quality operation and fine management of the pumped storage power station.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, specifically to a method and system for analyzing and evaluating the operation of pumped storage power stations based on multi-source data. Background Technology

[0002] The power plant evaluation data comes from diverse sources, including structured data from the production management system, which requires calculation, statistics, and filtering; massive amounts of low-value data from real-time monitoring, which require filtering out high-value data using practical algorithms; and signal data from the monitoring system, which requires calculating effective measurements based on control signals. Based on this multi-source data, the power plant's operation is evaluated through data filtering, calculation, statistics, and categorized storage. Summary of the Invention

[0003] To address the shortcomings of existing technologies, this invention provides a method for operational analysis and evaluation of pumped-storage power stations based on multi-source data, comprising the following steps:

[0004] S1. Collect multi-source data

[0005] Collect operational indicator data, inspection data, monitoring data, and control signals;

[0006] S2. Data Storage

[0007] Based on the needs of the data analysis process, statistical analysis is performed on multi-source data, and the multi-source data is classified and stored according to the statistical results;

[0008] S3. Filter Data

[0009] Feature data is filtered from monitoring data according to user needs and visual analysis graphs are generated;

[0010] S4. Generate Analysis Report

[0011] An analysis report is generated based on visual analytics graphics and categorized multi-source data.

[0012] Furthermore, the categorized storage in S2 includes a data collection area, a data calculation area, and a monthly statistics area; the data calculation area stores maximum and minimum values, duration values, and statistical values; the monthly statistics area stores monthly and annual cumulative data and other quantity statistics data from the operational indicator data; and the data collection area stores all collected multi-source data.

[0013] Furthermore, the extreme value type includes daily or monthly maximum / minimum values ​​and fluctuations of monitoring data from equipment such as reservoir water level, generator stator temperature, and labyrinth ring temperature, as well as the month-end reservoir capacity; the duration value is based on equipment start / stop or switch signals.

[0014] Furthermore, the operational indicator data includes:

[0015] Monthly statistics and monthly cumulative values, including:

[0016] Monthly statistics are: data on the operation of each device in the current month;

[0017] The monthly cumulative value is the sum of monthly statistics from the beginning of the year to the current month.

[0018] Furthermore, the feature data is: data that meets the selected time conditions from the monitoring data.

[0019] Furthermore, the filtering methods for the data include automatic methods, setting a data range, selecting a quantity, using a hash function or setting a step size to select a specific number of values ​​to generate a radar chart or trend chart.

[0020] Furthermore, the analysis report determines the equipment status by comparing data from multiple sources and uses an unreliability function to calculate equipment fatigue. The calculation method is as follows:

[0021]

[0022] Where R(t) is the fatigue value; ΔXi is the year-on-year change rate, and n represents the nth year-on-year change; when R(t) is greater than the set value, a maintenance or equipment retirement suggestion is made.

[0023] A pumped-storage power station operation analysis and evaluation system based on multi-source data, characterized in that it includes:

[0024] Data acquisition adapters include indicator adapters for acquiring operational indicator data from production management systems, inspection adapters for acquiring inspection data, monitoring adapters for acquiring monitoring data from real-time systems, and control adapters for acquiring control signals from monitoring systems.

[0025] Data storage is used to store data in partitions after statistical analysis, according to the needs of the data analysis process.

[0026] The data filter automatically filters feature data based on monitoring data and configuration requirements, and generates visual analysis graphics and image configurations.

[0027] The report generator is used to generate summary suggestions and analysis reports based on the statistical results of the data storage and the graphical image configuration of the filter, combined with user requirements.

[0028] Furthermore, the data storage device supports data analysis and modification of data partitioning rules.

[0029] Furthermore, the data filter supports selecting desired feature data by configuring filtering conditions.

[0030] Beneficial effects

[0031] Compared with existing technologies, this invention can statistically analyze important information such as pumped storage power station operation indicators, unit trends, power transmission and transformation equipment status analysis, and equipment operation frequency. It can also display, analyze, and evaluate equipment status information, and further provide guidance for power station operation, so as to achieve high-quality operation and refined management of pumped storage power stations. Attached Figure Description

[0032] Figure 1 This is a flowchart of the workflow of the present invention;

[0033] Figure 2 For statistical charts of operational indicator data;

[0034] Figure 3 Feature data selected from monitoring data;

[0035] Figure 4 This is a radar chart from the analysis report. Detailed Implementation

[0036] 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 embodiments of the present invention, and not all embodiments. 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.

[0037] Please see Figures 1-4 A method for analyzing and evaluating the operation of pumped storage power stations based on multi-source data includes the following steps:

[0038] S1. Collect multi-source data, including operational indicator data, inspection data, monitoring data, and control signals.

[0039] Operational indicator data includes power generation, pumped water volume, grid-connected power volume, power generation operation time, equipment defects, work permits, equipment scheduled inspections, and maintenance data. Operational indicator data can be stored in monthly units and accumulated monthly indicator values, as well as annual cumulative values ​​from the beginning of the year to the current month, enabling one-time calculation. Monitoring and surveillance data includes reservoir water level, unit bearing temperature, generator stator temperature, unit swing, unit vibration, oil pump outlet pressure, main transformer oil chromatography, and main transformer oil temperature data. Equipment start-up and shutdown data includes signal data such as the start-up and shutdown or switching time of important equipment and the number of equipment start-ups and shutdowns. Inspection data includes unit bearing oil level, technical water supply flow rate, lightning rod leakage current, lightning rod operation frequency, SF6 gas chamber pressure, and plant transformer pressure inspection and patrol record data.

[0040] S2. Data storage: Collected multi-source data is statistically analyzed and classified for storage. According to the needs of the data analysis process, the multi-source data is statistically analyzed and divided into the collected data area, the calculated data area, and the monthly statistics area according to the statistical results. The multi-source data is stored in the corresponding classification area.

[0041] The calculation data area stores extreme values, duration values, and statistical values. The extreme value types include daily or monthly maximum / minimum values ​​and fluctuations of monitoring data from equipment such as reservoir water level, generator stator temperature, and labyrinth ring temperature, as well as the month-end reservoir capacity. The duration values ​​are based on equipment start / stop or switch signals, such as the hydraulic locking engagement / disengagement time of ball valves and the opening / closing time of ball valve bypass valves. The monthly statistics area includes monthly and annual cumulative data from operational indicators, as well as quantity statistics for defects, work orders, etc.

[0042] S3. Data Filtering: Based on user needs, the system filters the monitoring data to extract characteristic data and generates visual analysis graphs, such as radar charts and line graphs. Characteristic data is selected from the monitoring data by configuring time conditions, or other conditions can be configured according to user requirements. Filtering methods include automatic mode, where the system sets the data range and selection quantity, and uses a hash function or sets a step size to select a specific number of values ​​for generating radar charts or trend graphs.

[0043] S4. Generate an analysis report. The analysis report is generated based on the visual analysis graphics and the categorized multi-source data. One principle summarized and suggested in the analysis report is to determine the equipment status by comparing the monitoring data month-on-month, and to calculate the equipment fatigue using an unreliability function. The calculation method is as follows:

[0044]

[0045] Where R(t) is the fatigue value; ΔXi is the year-on-year change rate, and n represents the nth year-on-year change; when R(t) is greater than the set value, a maintenance or equipment retirement suggestion is made.

[0046] Example 2

[0047] A pumped-storage power station operation analysis and evaluation system based on multi-source data includes,

[0048] The data acquisition adapters include an indicator adapter for acquiring operational indicator data from the production management system, an inspection adapter for acquiring inspection data, a monitoring adapter for acquiring monitoring data from the real-time system, and a control adapter for acquiring control signals from the monitoring system.

[0049] The data storage device performs statistical analysis and partitioned storage of data according to the needs of the data analysis process, and supports data analysis and modification of data partitioning rules.

[0050] The data filter automatically filters feature data based on monitoring data and configuration requirements, and generates visual analysis graphics and image configurations; the data filter supports selecting the required feature data by configuring filtering conditions.

[0051] The report generator is used to generate image configurations based on statistical results from the data storage and feature data filtered by the filter, and to generate summary and suggestion information and analysis reports in accordance with user requirements.

[0052] Example 3

[0053] This embodiment illustrates the operation of the invention through actual operation, and the steps are as follows:

[0054] 1. By configuring communication parameters, start the operation indicator data adapter, inspection data adapter, monitoring data adapter, and control signal adapter to acquire raw data.

[0055] 2. In the Operational Indicator Data Adapter, users select the indicators they need to query and analyze on the page, including power generation, pumping power, grid connection power, number of power generation starts, number of pumping starts, number of power generation operations, number of pumping operations, power generation operation time, pumping operation time, power generation, pumping power, equipment defects, work orders, equipment scheduled inspections, maintenance, etc. The configuration information is stored in the data storage device through the Operational Indicator Data Adapter. When the query data button is clicked, the Operational Indicator Data Adapter retrieves the relevant indicator information from the hydropower production management system based on the previous configuration information and generates monthly statistical charts through the statistical calculation and analysis unit.

[0056] 3. Monitoring data include reservoir water level, generator bearing temperature, generator stator temperature, generator set switching, generator set vibration, oil pump outlet pressure, main transformer oil chromatography, and main transformer oil temperature, etc.

[0057] The monitoring data consists of characteristic data collected from massive datasets. The selection of characteristic data is based on monitoring signals such as equipment control signals or reservoir water levels, and is achieved by configuring time conditions. For example, the temperature of the upper guide plate of the generator is measured 60 minutes after the generator starts up. If a shutdown signal is detected within 60 minutes, the measurement value at the time of shutdown is taken. Similarly, for the swing of unit components during pumping, the water head position needs to be recorded simultaneously, and the component swing curve during pumping needs to be collected.

[0058] The reservoir water level requires the selection of date, upper reservoir water level label, and lower reservoir water level label. The detection data adapter obtains water level data from a massive time series database and the real-time hydropower system. The water level data is then used by a statistical calculation analyzer to calculate the highest operating water level, maximum water level fluctuation, month-end reservoir capacity, year-on-year and month-on-month data, and finally stored in the data storage device.

[0059] The unit bearing temperature module is equipped with tags for the top bearing temperature of the generator and the top bearing temperature of the pumping unit. The generator or pumping operation signals of each unit are obtained through the monitoring signal adapter. The monitoring data adapter obtains the temperature data of different locations of each unit from a massive time series library. The maximum value is calculated by the statistical calculation analyzer. A specific number of values ​​are selected using a hash function or by setting a step size to generate a radar chart or trend chart.

[0060] 4. The equipment start-up and shutdown data in the monitoring data includes signal data such as the start-up and shutdown or switching time of important equipment and the number of times the equipment starts and stops. The start-up and shutdown of important equipment is achieved by using a control signal adapter to input the corresponding signal points required by the monitoring system into the real-time hydropower system. Data is generated by judging the time difference between two signals and then stored in the database. Examples include the hydraulic locking activation / deactivation time of ball valves, the opening and closing time of ball valve bypass valves, the activation / deactivation time of ball valve working seals, the opening and closing time of ball valves, the hydraulic locking activation / deactivation time of guide vanes, the opening and closing time of important valves, the phase-adjusting pressure water time, and the return water venting time.

[0061] 5. Inspection data includes unit bearing oil level, technical water supply flow, lightning rod leakage current, lightning rod operation frequency, SF6 gas chamber pressure, and plant transformer pressure inspection records, etc. Users obtain relevant data from the hydropower production management system through the inspection data adapter, store the data in the data storage device, and calculate the statistical data through the statistical calculation and analysis unit.

[0062] 6. Generate analysis report: Based on user-specified configuration and defined template, the data collector acquires the data calculated by the statistical analysis unit, automatically filters out feature data through the data filter, generates visual analysis graphics configuration, and fills the data into the template to generate analysis report.

[0063] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0064] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for analyzing and evaluating the operation of pumped-storage power stations based on multi-source data, characterized in that: Includes the following steps: S1. Collect multi-source data Collect operational indicator data, inspection data, monitoring data, and control signals; S2. Data Storage Based on the needs of the data analysis process, statistical analysis is performed on multi-source data, and the multi-source data is classified and stored according to the statistical results; S3. Filter Data Feature data is filtered from monitoring data according to user needs and visual analysis graphs are generated; S4. Generate Analysis Report An analysis report is generated based on visual analytics graphics and categorized multi-source data.

2. The method for operation analysis and evaluation of pumped storage power stations based on multi-source data as described in claim 1, characterized in that: The categorized storage in S2 includes a data collection area, a data calculation area, and a monthly statistics area; The calculation data area stores extreme values, duration values, and statistical values; the monthly statistics area stores monthly and annual cumulative data and other quantitative statistical data from the operational indicator data; and the collected data area stores all collected multi-source data.

3. The method for operation analysis and evaluation of pumped storage power stations based on multi-source data as described in claim 2, characterized in that: The maximum / minimum value types include daily or monthly maximum / minimum values ​​and fluctuations of monitoring data from equipment such as reservoir water level, generator stator temperature, and labyrinth ring temperature, as well as the month-end reservoir capacity; the duration value is based on equipment start / stop or switch signals.

4. The method for operation analysis and evaluation of pumped storage power stations based on multi-source data as described in claim 1, characterized in that: The operational metrics data include: Monthly statistics and monthly cumulative values, including: Monthly statistics are: data on the operation of each device in the current month; The monthly cumulative value is the sum of monthly statistics from the beginning of the year to the current month.

5. The method for operation analysis and evaluation of pumped storage power stations based on multi-source data as described in claim 1, characterized in that: The feature data is: data that meets the selected time conditions from the monitoring data.

6. The method for operation analysis and evaluation of pumped storage power stations based on multi-source data as described in claim 1, characterized in that: The data filtering methods include automatic methods, setting a data range, selecting a quantity, using a hash function or setting a step size to select a specific number of values ​​to generate a radar chart or trend chart.

7. The method for analysis and evaluation of pumped-storage power station operation based on multi-source data as described in claim 1, characterized in that: The analysis report uses a month-on-month comparison of multi-source data to determine the equipment status and employs an unreliability function to calculate equipment fatigue. The calculation method is as follows: Where R(t) is the fatigue value; ΔXi is the year-on-year change rate, and n represents the nth year-on-year change; when R(t) is greater than the set value, a maintenance or equipment retirement suggestion is made.

8. A pumped-storage power station operation analysis and evaluation system based on multi-source data, characterized in that: include, Data acquisition adapters include indicator adapters for acquiring operational indicator data from production management systems, inspection adapters for acquiring inspection data, monitoring adapters for acquiring monitoring data from real-time systems, and control adapters for acquiring control signals from monitoring systems. Data storage is used to store data in partitions after statistical analysis, according to the needs of the data analysis process. The data filter automatically filters feature data based on monitoring data and configuration requirements, and generates visual analysis graphics and image configurations. The report generator is used to generate summary suggestions and analysis reports based on the statistical results of the data storage and the graphical image configuration of the filter, combined with user requirements.

9. The pumped-storage power station operation analysis and evaluation system based on multi-source data as described in claim 8, characterized in that: The data storage device supports data analysis and modification of data partitioning rules.

10. The pumped-storage power station operation analysis and evaluation system based on multi-source data as described in claim 8, characterized in that: The data filter allows users to select desired feature data by configuring filtering conditions.

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