Pumped storage equipment state real-time evaluation system and method based on data analysis

Abstract

The invention discloses a pumped storage equipment state real-time evaluation system and method based on data analysis, and relates to the technical field of big data analysis. A PLC control system is combined with an OPC single unit rotating speed fluctuation peak value UA protocol and a reluctance type rotating speed sensor to obtain historical and real-time unit rotating speed data respectively, a first set of equipment state analysis and a second set of real-time equipment state analysis are constructed, and then through data traversal analysis, weight fusion calculation and a time sequence prediction model, the real-time unit rotating speed data are obtained. A fluctuation peak value, a standard unit rotating speed and a rotating speed change trend are obtained, a unit rotating speed upper limit value and the standard unit rotating speed are combined for monitoring, an analysis set is constructed according to monitoring results, the trend is predicted, and accurate capture of unit rotating speed fluctuation characteristics of the pumped storage equipment, dynamic evaluation of the running state and abnormal early warning are achieved. The data reliability and the analysis accuracy are improved, and support is provided for equipment state monitoring.

Description

Technical Field

[0001] The present invention relates to the technical field of big data analysis, and in particular to a system and method for real-time evaluation of the status of pumped storage equipment based on data analysis. Background Art

[0002] Pumped storage equipment is a core facility for the flexible storage and regulation of electrical energy in power systems. It plays a key role in ensuring stable grid operation, improving renewable energy absorption capacity, and optimizing the energy mix. Its importance lies in its ability to effectively smooth grid load fluctuations, enhance power supply reliability, and mitigate operational risks associated with peak-to-valley fluctuations. It also provides peak-shaving and frequency-regulating support for the large-scale integration of renewable energy sources into the grid.

[0003] The speed of pumped-storage hydroelectric generator sets is affected by multiple factors, including grid load fluctuations, unit start-up and shutdown switching, changes in water flow conditions, and mechanical wear. Its stability directly determines the unit's operating efficiency and energy conversion accuracy. Abnormal speeds can lead to increased vibration, accelerated component wear, and even downtime, impacting the grid's peak and frequency regulation capabilities, renewable energy absorption efficiency, and the safety and reliability of the power system. Therefore, a real-time dynamic analysis method for speed assessment is urgently needed to accurately capture speed fluctuations and predict equipment operating status, providing technical support for the safe and efficient operation of pumped-storage hydroelectric generators and intelligent grid control. Summary of the Invention

[0004] The purpose of the present invention is to provide a real-time evaluation system and method for the status of pumped storage equipment based on data analysis, so as to solve the problems raised in the prior art.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for real-time evaluation of the status of a pumped storage device based on data analysis, the method comprising the following steps: Step S1: Set a unit speed data collection period, obtain historical unit speed data of each pumped storage device to construct a first set of equipment status analysis; obtain unit speed data of each pumped storage device within the unit speed data collection period to construct a second set of real-time equipment status analysis; Step S1-1, using the data export tool of the PLC control system in conjunction with the OPC single unit speed fluctuation peak UA interface protocol, historical unit speed data of each pumped storage device in the current unit speed data acquisition cycle is acquired, where the unit speed data is expressed as the number of rotations of the main shaft of the pumped storage device per unit time; Step S1-2: Select the unique identifier of the pumped storage equipment as the primary key, and store the unit speed data corresponding to the timestamp as the value to construct a first set of equipment status analysis; Step S1-3, obtaining the unit speed data of the pumped storage equipment during the data acquisition period through the magnetoresistive speed sensor, and constructing a second set of real-time equipment status analysis according to the storage method of step S1-2; By setting the data collection cycle, combining the PLC control system with the OPC single unit speed fluctuation peak UA protocol to obtain historical data, and using the magnetoresistive speed sensor to collect real-time data, the first set of equipment status analysis and the second set of real-time equipment status analysis are constructed for equipment status analysis. This can not only perform trend analysis and fault prediction based on historical data, but also realize real-time monitoring of equipment operating status based on real-time data, so as to comprehensively, accurately and efficiently grasp the speed of pumped storage equipment units and ensure the safe and stable operation of the equipment.

[0006] Step S2: performing data traversal analysis based on the first set of equipment status analysis to obtain the fluctuation peak value of the unit speed data; and performing weighted fusion calculation based on the first set of equipment status analysis and the second set of real-time equipment status analysis to obtain the standard unit speed of the pumped storage equipment within the current unit speed data collection period; Step S2-1, traversing and reading the unit speed data in the first set of device state analysis, calculating the absolute value of the difference between two sets of unit speed data at adjacent moments in the first set of device state analysis, and selecting the maximum absolute value of the pumped storage device unit speed through a bubble sort algorithm, recording it as the comprehensive unit speed fluctuation peak value. The comprehensive unit speed fluctuation peak value is represented by the maximum instantaneous fluctuation of the number of revolutions of the main shaft of the pumped storage device unit per unit time between two adjacent sampling moments during the operation of the unit; Step S2-2: Calculate the average value of the unit speed data in the first set of equipment status analysis, which is recorded as the first unit speed average value; calculate the average value of the unit speed data in the second set of real-time equipment status analysis, which is recorded as the second unit speed average value; Step S2-3: Obtain the standard unit speed of the pumped storage equipment within the current unit speed data collection period by performing weighted fusion calculation based on the average speed of the first unit and the average speed of the second unit; The standard unit speed of pumped storage equipment is calculated using the following formula: ; Where S tandard represents the standard unit speed of the pumped storage equipment; a represents the weighting coefficient of the weighted fusion calculation, with a value range of 0≤w≤1; n represents the number of samples of the unit speed data in the first set of equipment status analysis; V h，i Represented as the first set V of device state analysis h The speed value of the unit at the i-th time point in the real-time equipment status analysis; m represents the number of samples of the unit speed data in the second set; Vr，i Expressed as the second set V for real-time device status analysis r The unit speed value at the i-th time point in ; This calculation method obtains the peak value of the unit speed fluctuation through traversal analysis, grasps the instantaneous fluctuation status of the unit operation, and then calculates the mean value by combining historical data and real-time data. It uses weighted fusion to obtain the standard unit speed. It takes into account both the stability of historical data and the dynamic nature of real-time data. It can accurately reflect the true state of the unit speed of pumped storage equipment, effectively improve data reliability and analysis accuracy, and provide strong support for equipment operation status monitoring and fault diagnosis.

[0007] Step S3: Acquire historical unit speed data based on the unique identifier of the pumped storage equipment to construct a single unit speed analysis set, analyze the single unit speed analysis set to obtain the unit speed change trend of the pumped storage equipment, and extract the maximum fluctuation of the single unit speed, which is recorded as the single unit speed fluctuation peak value; Step S3-1: Select the unique identifier of any pumped-storage equipment within the current unit speed data collection period as an index, extract the historical unit speed data of the corresponding pumped-storage equipment from the first device status analysis set using the index, and construct a single-unit speed analysis set according to the storage method of step S1-2. The single-unit speed analysis set is specifically an independent data set established for each pumped-storage equipment. The set uses the device unique identifier as the primary key index, and associates and stores all unit speed data within each unit speed data collection period to form a one-to-one mapping time series data structure. Step S3-2: using a time series prediction model through a single unit speed analysis set to predict the speed change trend of the pumped storage equipment; Step S3-3, traversing and reading the unit speed data in the single unit speed analysis set, calculating the absolute value of the difference between the speed data of two sets of units at adjacent moments as the maximum value of the speed fluctuation of a single unit of the pumped storage equipment, recorded as the peak value of the speed fluctuation of a single unit; By constructing a single-unit speed analysis set, using a time series prediction model to analyze the speed change trend, and extracting the maximum value of a single speed fluctuation, we can not only predict the equipment operation direction, but also capture the instantaneous fluctuation extremes, providing data support for accurately grasping equipment performance and early warning of abnormal fluctuations, thereby improving equipment operation stability and maintenance efficiency.

[0008] Step S4: obtaining a unit speed overspeed value of the pumped-storage equipment based on the unit speed change trend and a single unit speed fluctuation peak value; monitoring the unit speed overspeed value using a standard unit speed of the pumped-storage equipment, monitoring the pumped-storage equipment based on the unit speed overspeed value and the standard unit speed, and storing and constructing a unit speed analysis set based on the monitoring results; Step S4-1, calculating the average speed of the pumped storage equipment based on the predicted speed change trend of the equipment to obtain the average speed of the equipment; Step S4-2: Using the comprehensive unit speed fluctuation peak value and the single unit speed fluctuation peak value, a weighted fusion calculation is performed to obtain a standard unit speed fluctuation peak value for the pumped storage equipment. The standard unit speed fluctuation peak value is represented by the instantaneous maximum number of revolutions of the unit main shaft per unit time when the pumped storage equipment is affected by negative fluctuation factors during operation. The peak value of the standard unit speed fluctuation of pumped storage equipment is calculated using the following formula: ; Where, F tandard It represents the peak value of the speed fluctuation of the standard unit of the pumped storage equipment; w represents the weighting coefficient in the weighted fusion calculation of the peak value of the speed fluctuation of the standard unit, and its value range is 0≤w≤1; F max It is expressed as the peak value of the comprehensive unit speed fluctuation of the pumped storage equipment; F single It is expressed as the peak value of speed fluctuation of a single unit of pumped storage equipment; Step S4-3: Calculate an upper limit of the unit speed by adding the average unit speed of the pumped storage equipment to the peak value of the standard unit speed fluctuation. The upper limit of the unit speed represents the maximum limit value that the unit speed of the pumped storage equipment is allowed to reach under safe operating conditions. The upper limit of the unit speed of the pumped storage equipment is calculated using the following formula: ; Where, f tandard Expressed as the peak value of the standard unit speed fluctuation of the pumped storage equipment; F avg It is expressed as the average speed of the pumped storage equipment in the single unit speed analysis set.

[0009] Step S4-4: Monitor the pumped storage equipment using the upper limit of the unit speed and the standard unit speed, and perform data analysis and processing on the monitoring results to form a unit speed analysis set. The specific process of the data analysis and processing is as follows: Step S4-4-1, using the upper limit value of the unit speed of the pumped storage equipment minus the standard unit speed, performing absolute value processing on the obtained difference to obtain the absolute value deviation of the upper limit of the unit speed from the standard value; Step S4-4-2: Select the timestamp data of the pumped storage equipment as the primary key, select the absolute value deviation of the upper limit of the unit speed from the standard value as the value, and store them after time series arrangement to construct a unit speed analysis set; By combining the speed change trend of the unit with the single peak value to calculate the overspeed value, and monitoring based on the standard speed, we can not only determine the limit threshold for safe operation of the pumped storage equipment, but also quantify the degree of speed fluctuation deviation. The resulting unit speed analysis set can intuitively reflect the equipment status change trend, provide a data basis for the precise control and preventive maintenance of the equipment, and ensure the efficient and stable operation of the pumped storage equipment.

[0010] Step S5: Predicting the speed change trend of the pumped storage equipment through the group speed analysis set analysis; and evaluating and warning the pumped storage equipment based on the speed change trend of each pumped storage equipment within the current unit speed data collection period; Step S5-1, traverse and read the absolute deviation of the upper limit of the unit speed from the standard value in the group speed analysis set, and input it into the time series prediction model in turn to analyze and predict the change trend of the unit speed of the pumped storage equipment; Step S5-2: using the data analysis process from step S3 to step S4, obtaining the speed change trend of each pumped storage device within the current speed data collection period; Step S5-3: extract the unit speed value corresponding to the maximum value of the horizontal coordinate in the speed change trend of the pumped storage equipment, compare the extracted unit speed value with the upper limit of the unit speed, and evaluate and warn the pumped storage equipment based on the comparison and judgment result. The specific process of the comparison and judgment is as follows: Step S5-3-1: When the speed of the pumped storage equipment exceeds the upper limit of the speed, it is determined that the speed of the equipment is abnormal and an early warning signal is issued; Step S5-3-2: When the speed value of the pumped storage equipment unit does not exceed the upper limit of the speed value of the unit, it is determined that the speed of the unit is normal, no warning signal is issued, and the speed of the unit is continuously monitored; By analyzing the unit speed analysis set through a time series prediction model and combining the results of multi-stage data analysis, the speed change trend of each device is obtained. The predicted extreme values ​​are compared with the safety threshold to achieve dynamic early warning of the operating status of the pumped storage equipment. This can not only detect speed anomalies in time to avoid equipment damage, but also ensure the efficient and stable operation of the equipment through continuous monitoring, thereby improving the safety and reliability of the pumped storage system.

[0011] Furthermore, a real-time evaluation system for the status of pumped storage equipment based on data analysis is provided, wherein the real-time evaluation system for the status of pumped storage equipment includes a data acquisition module, a data processing module, a single-machine analysis module, a threshold monitoring module, and an evaluation and early warning module; The data acquisition module is used to obtain historical and real-time unit speed data of the pumped storage equipment and construct a collection; the data processing module is used to calculate and analyze the collected historical and real-time data and generate a standard unit speed; the single-machine analysis module is used to predict the speed trend based on the historical data of the single machine and analyze the fluctuation characteristics; the threshold monitoring module is used to combine the speed mean and peak values ​​to calculate the unit safe operation threshold and analyze the deviation; the evaluation and warning module is used to predict future trends based on the deviation data and trigger abnormal warnings; The output end of the data acquisition module is electrically connected to the input end of the data processing module; the output end of the data processing module is electrically connected to the input end of the stand-alone analysis module; the output end of the stand-alone analysis module is electrically connected to the input end of the threshold monitoring module; the output end of the threshold monitoring module is electrically connected to the input end of the evaluation and early warning module; The data acquisition module includes a historical data acquisition unit and a real-time data acquisition unit; the historical data acquisition unit is used to obtain the historical unit speed data of the pumped storage equipment through the PLC control system and the OPC single unit speed fluctuation peak UA protocol; the real-time data acquisition unit is used to obtain the real-time unit speed data of the pumped storage equipment in the current cycle through the magnetoresistive speed sensor; The data processing module includes a peak calculation unit and a mean fusion unit; the peak calculation unit is used to traverse historical data and calculate the peak value of the comprehensive unit speed fluctuation of the pumped storage equipment through a bubble sort algorithm; the mean fusion unit is used to calculate the average value of historical and real-time data and generate a standard unit speed through weighted fusion; The single-machine analysis module includes a trend prediction unit and a fluctuation analysis unit; the trend prediction unit is used to predict the speed change trend of the pumped storage equipment through a time series model; the fluctuation analysis unit is used to calculate the absolute value of the speed difference between adjacent moments of the single machine and extract the peak value of the single unit speed fluctuation; The threshold monitoring module includes a threshold calculation unit and a deviation analysis unit; the threshold calculation unit is used to calculate the safe operation upper limit of the pumped storage equipment by combining the average speed of the unit and the standard peak value; the deviation analysis unit is used to compare the speed upper limit with the standard speed, and calculate the deviation to store and construct an analysis set; The evaluation and early warning module includes a trend prediction unit and an early warning trigger unit; the trend prediction unit is used to predict the future speed change trend of the pumped storage equipment based on historical deviation data; the early warning trigger unit is used to compare the real-time speed with the upper limit value, judge the unit status and trigger abnormal early warning or continuous monitoring.

[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. By constructing a multi-dimensional data analysis system and comprehensively utilizing historical data and real-time data, the present invention can not only accurately capture the speed fluctuation characteristics of pumped-storage equipment units, but also dynamically predict the speed change trend, providing comprehensive and reliable data support for the evaluation of the operating status of pumped-storage equipment, and significantly improving the accuracy and foresight of the evaluation results.

[0013] 2. This invention combines historical stability with real-time dynamics to scientifically calculate the standard unit speed and fluctuation peak value, effectively quantifying the degree of deviation in the equipment operating status, providing clear and specific reference indicators for pumped storage equipment monitoring and early warning, and enhancing the scientific nature and practicality of the evaluation system.

[0014] 3. The present invention establishes an intelligent early warning mechanism and predicts speed anomalies in advance based on a time series prediction model, thereby achieving preventive maintenance of pumped storage equipment. This can not only avoid sudden failures of pumped storage equipment, but also optimize equipment operation and maintenance plans, greatly improving the operational safety and economy of pumped storage equipment, and effectively ensuring the stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A flow chart of a method for real-time evaluation of pumped storage equipment status based on data analysis according to the present invention; Figure 2 The diagram is a structural diagram of a real-time evaluation system for pumped storage equipment status based on data analysis according to the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] Example 1: Figure 1 As shown, the present invention provides a technical solution, a real-time evaluation method for the status of a pumped storage device based on data analysis, and the real-time evaluation method for the status of a pumped storage device comprises the following steps: Step S1: Set a unit speed data collection period, obtain historical unit speed data of each pumped storage device to construct a first set of equipment status analysis; obtain unit speed data of each pumped storage device within the unit speed data collection period to construct a second set of real-time equipment status analysis; Step S1-1, using the data export tool of the PLC control system in conjunction with the OPC single unit speed fluctuation peak UA interface protocol, historical unit speed data of each pumped storage device in the current unit speed data acquisition cycle is acquired, where the unit speed data is expressed as the number of rotations of the main shaft of the pumped storage device per unit time; Step S1-2: Select the unique identifier of the pumped storage equipment as the primary key, and store the unit speed data corresponding to the timestamp as the value to construct a first set of equipment status analysis; Step S1-3, obtaining the unit speed data of the pumped storage equipment during the data acquisition period through the magnetoresistive speed sensor, and constructing a second set of real-time equipment status analysis according to the storage method of step S1-2; In specific implementation, the data export tool of the PLC control system is combined with the OPC single unit speed fluctuation peak UA interface protocol to batch pull the unit speed data of each device per minute in the past hour from the historical database, such as 1000r / min, 1005r / min, etc. to build the first set of equipment status analysis. At the same time, the magnetoresistive speed sensor is used to collect the current speed data per minute in real time to build the second set. The principle is to use industrial protocols to achieve efficient acquisition of historical data and sensors to achieve real-time data collection. Step S2: performing data traversal analysis based on the first set of equipment status analysis to obtain the fluctuation peak value of the unit speed data; and performing weighted fusion calculation based on the first set of equipment status analysis and the second set of real-time equipment status analysis to obtain the standard unit speed of the pumped storage equipment within the current unit speed data collection period; Step S2-1, traversing and reading the unit speed data in the first set of device state analysis, calculating the absolute value of the difference between two sets of unit speed data at adjacent moments in the first set of device state analysis, and selecting the maximum absolute value of the pumped storage device unit speed through a bubble sort algorithm, recording it as the comprehensive unit speed fluctuation peak value. The comprehensive unit speed fluctuation peak value is represented by the maximum instantaneous fluctuation of the number of revolutions of the main shaft of the pumped storage device unit per unit time between two adjacent sampling moments during the operation of the unit; Step S2-2: Calculate the average value of the unit speed data in the first set of equipment status analysis, which is recorded as the first unit speed average value; calculate the average value of the unit speed data in the second set of real-time equipment status analysis, which is recorded as the second unit speed average value; Step S2-3: Obtain the standard unit speed of the pumped storage equipment within the current unit speed data collection period by performing weighted fusion calculation based on the average speed of the first unit and the average speed of the second unit; In the specific implementation, taking the speed data of 10 consecutive single unit speed fluctuation peaks of a certain unit (1000, 1008, 1003, 995, 1010...) as an example, the single unit speed fluctuation peak of 15r / min with the largest adjacent difference is found through bubble sorting as the comprehensive fluctuation peak, and then the standard speed (such as the single unit speed fluctuation peak of 1002r / min) is calculated using the mean of historical data (weighted single unit speed fluctuation peak 0.6) and the mean of real-time data (weighted single unit speed fluctuation peak 0.4); the principle is to improve accuracy through the dynamic fusion of statistical characteristics of historical data and real-time data.

[0018] Step S3: Acquire historical unit speed data based on the unique identifier of the pumped storage equipment to construct a single unit speed analysis set, analyze the single unit speed analysis set to obtain the unit speed change trend of the pumped storage equipment, and extract the maximum fluctuation of the single unit speed, which is recorded as the single unit speed fluctuation peak value; Step S3-1: Select the unique identifier of any pumped-storage equipment within the current unit speed data collection period as an index, extract the historical unit speed data of the corresponding pumped-storage equipment from the first device status analysis set using the index, and construct a single-unit speed analysis set according to the storage method of step S1-2. The single-unit speed analysis set is specifically an independent data set established for each pumped-storage equipment. The set uses the device unique identifier as the primary key index, and associates and stores all unit speed data within each unit speed data collection period to form a one-to-one mapping time series data structure. Step S3-2: using a time series prediction model through a single unit speed analysis set to predict the speed change trend of the pumped storage equipment; Step S3-3, traversing and reading the unit speed data in the single unit speed analysis set, calculating the absolute value of the difference between the speed data of two sets of units at adjacent moments as the maximum value of the speed fluctuation of a single unit of the pumped storage equipment, recorded as the peak value of the speed fluctuation of a single unit; In specific implementation, for example, for unit PS-001, its speed data for the past 24 hours is extracted to construct a single-machine analysis set. The ARIMA model is used to predict that the speed will show an upward trend in the next two hours. At the same time, the maximum difference between adjacent moments, 20r / min, is calculated as the single fluctuation peak. Trend prediction is achieved based on time series modeling of single-machine historical data.

[0019] Step S4: obtaining a unit speed overspeed value of the pumped-storage equipment based on the unit speed change trend and a single unit speed fluctuation peak value; monitoring the unit speed overspeed value using a standard unit speed of the pumped-storage equipment, monitoring the pumped-storage equipment based on the unit speed overspeed value and the standard unit speed, and storing and constructing a unit speed analysis set based on the monitoring results; Step S4-1, calculating the average speed of the pumped storage equipment based on the predicted speed change trend of the equipment to obtain the average speed of the equipment; Step S4-2: Using the comprehensive unit speed fluctuation peak value and the single unit speed fluctuation peak value, a weighted fusion calculation is performed to obtain a standard unit speed fluctuation peak value for the pumped storage equipment. The standard unit speed fluctuation peak value is represented by the instantaneous maximum number of revolutions of the unit main shaft per unit time when the pumped storage equipment is affected by negative fluctuation factors during operation. Step S4-3: Calculate an upper limit of the unit speed by adding the average unit speed of the pumped storage equipment to the peak value of the standard unit speed fluctuation. The upper limit of the unit speed represents the maximum limit value that the unit speed of the pumped storage equipment is allowed to reach under safe operating conditions. Step S4-4: Monitor the pumped storage equipment using the upper limit of the unit speed and the standard unit speed, and perform data analysis and processing on the monitoring results to form a unit speed analysis set. The specific process of the data analysis and processing is as follows: Step S4-4-1, using the upper limit value of the unit speed of the pumped storage equipment minus the standard unit speed, performing absolute value processing on the obtained difference to obtain the absolute value deviation of the upper limit of the unit speed from the standard value; Step S4-4-2: Select the timestamp data of the pumped storage equipment as the primary key, select the absolute value deviation of the upper limit of the unit speed from the standard value as the value, and store them after time series arrangement to construct a unit speed analysis set; In specific implementation, a unit predicts a mean of 1005r / min, a comprehensive fluctuation peak of 15r / min, and a single fluctuation peak of 20r / min, with weights of 0.7 and 0.3 respectively. The standard fluctuation peak is calculated to be 16.5r / min, and the speed upper limit is 1021.5r / min. When monitoring the current speed of 1018r / min, the deviation of 3.5r / min is calculated and stored; the safety threshold is set by superimposing the mean and the fluctuation peak.

[0020] Step S5: Predicting the speed change trend of the pumped storage equipment through the group speed analysis set analysis; and evaluating and warning the pumped storage equipment based on the speed change trend of each pumped storage equipment within the current unit speed data collection period; Step S5-1, traverse and read the absolute deviation of the upper limit of the unit speed from the standard value in the group speed analysis set, and input it into the time series prediction model in turn to analyze and predict the change trend of the unit speed of the pumped storage equipment; Step S5-2: using the data analysis process from step S3 to step S4, obtaining the speed change trend of each pumped storage device within the current speed data collection period; Step S5-3: extract the unit speed value corresponding to the maximum value of the horizontal coordinate in the speed change trend of the pumped storage equipment, compare the extracted unit speed value with the upper limit of the unit speed, and evaluate and warn the pumped storage equipment based on the comparison and judgment result. The specific process of the comparison and judgment is as follows: Step S5-3-1: When the speed of the pumped storage equipment exceeds the upper limit of the speed, it is determined that the speed of the equipment is abnormal and an early warning signal is issued; Step S5-3-2: When the speed value of the pumped storage equipment unit does not exceed the upper limit of the speed value of the unit, it is determined that the speed of the unit is normal, no warning signal is issued, and the speed of the unit is continuously monitored; In specific implementation, taking the predicted speed curve of a certain unit in the next hour as an example, the terminal speed value 1025r / min is extracted and compared with the upper limit value 1021.5r / min. When the limit is exceeded, an audible and visual warning is triggered; the principle is to achieve advanced warning by comparing the predicted value with the threshold. It should be noted that the time series prediction model needs to be regularly updated with the latest data.

[0021] Example 2, as Figure 2 As shown, the present invention provides a real-time evaluation system for the status of pumped storage equipment based on data analysis, which includes a data acquisition module, a data processing module, a stand-alone analysis module, a threshold monitoring module and an evaluation and early warning module; The data acquisition module is used to obtain historical and real-time unit speed data of the pumped storage equipment and construct a collection; the data processing module is used to calculate and analyze the collected historical and real-time data and generate a standard unit speed; the single-machine analysis module is used to predict the speed trend based on the historical data of the single machine and analyze the fluctuation characteristics; the threshold monitoring module is used to combine the speed mean and peak values ​​to calculate the unit safe operation threshold and analyze the deviation; the evaluation and warning module is used to predict future trends based on the deviation data and trigger abnormal warnings; The output end of the data acquisition module is electrically connected to the input end of the data processing module; the output end of the data processing module is electrically connected to the input end of the stand-alone analysis module; the output end of the stand-alone analysis module is electrically connected to the input end of the threshold monitoring module; the output end of the threshold monitoring module is electrically connected to the input end of the evaluation and early warning module; The data acquisition module includes a historical data acquisition unit and a real-time data acquisition unit; the historical data acquisition unit is used to obtain the historical unit speed data of the pumped storage equipment through the PLC control system and the OPC single unit speed fluctuation peak UA protocol; the real-time data acquisition unit is used to obtain the real-time unit speed data of the pumped storage equipment in the current cycle through the magnetoresistive speed sensor; The data processing module includes a peak calculation unit and a mean fusion unit; the peak calculation unit is used to traverse historical data and calculate the peak value of the comprehensive unit speed fluctuation of the pumped storage equipment through a bubble sort algorithm; the mean fusion unit is used to calculate the average value of historical and real-time data and generate a standard unit speed through weighted fusion; The single-machine analysis module includes a trend prediction unit and a fluctuation analysis unit; the trend prediction unit is used to predict the speed change trend of the pumped storage equipment through a time series model; the fluctuation analysis unit is used to calculate the absolute value of the speed difference between adjacent moments of the single machine and extract the peak value of the single unit speed fluctuation; The threshold monitoring module includes a threshold calculation unit and a deviation analysis unit; the threshold calculation unit is used to calculate the safe operation upper limit of the pumped storage equipment by combining the average speed of the unit and the standard peak value; the deviation analysis unit is used to compare the speed upper limit with the standard speed, and calculate the deviation to store and construct an analysis set; The evaluation and early warning module includes a trend prediction unit and an early warning trigger unit; the trend prediction unit is used to predict the future speed change trend of the pumped storage equipment based on historical deviation data; the early warning trigger unit is used to compare the real-time speed with the upper limit value, judge the unit status and trigger abnormal early warning or continuous monitoring.

[0022] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A real-time evaluation method for pumped storage equipment status based on data analysis, characterized by: The method for real-time evaluation of the state of a pumped storage device comprises the following steps: Step S1: Set a unit speed data collection period, obtain historical unit speed data of each pumped storage device to construct a first set of equipment status analysis; obtain unit speed data of each pumped storage device within the unit speed data collection period to construct a second set of real-time equipment status analysis; Step S2: performing data traversal analysis based on the first set of equipment status analysis to obtain the fluctuation peak value of the unit speed data; and performing weighted fusion calculation based on the first set of equipment status analysis and the second set of real-time equipment status analysis to obtain the standard unit speed of the pumped storage equipment within the current unit speed data collection period; Step S3: Acquire historical unit speed data based on the unique identifier of the pumped storage equipment to construct a single unit speed analysis set, analyze the single unit speed analysis set to obtain the unit speed change trend of the pumped storage equipment, and extract the maximum fluctuation of the single unit speed, which is recorded as the single unit speed fluctuation peak value; Step S4: obtaining a unit speed overspeed value of the pumped-storage equipment based on the unit speed change trend and a single unit speed fluctuation peak value; monitoring the unit speed overspeed value using a standard unit speed of the pumped-storage equipment, monitoring the pumped-storage equipment based on the unit speed overspeed value and the standard unit speed, and storing and constructing a unit speed analysis set based on the monitoring results; Step S5: Predict the speed change trend of the pumped storage equipment through the group speed analysis set analysis; and evaluate and warn the pumped storage equipment based on the speed change trend of each pumped storage equipment within the current unit speed data collection period.

2. A method for real-time assessment of pumped storage equipment status based on data analysis according to claim 1, characterized in that: The specific steps of step S1 are as follows: Step S1-1, using the data export tool of the PLC control system in conjunction with the OPC single unit speed fluctuation peak UA interface protocol, historical unit speed data of each pumped storage device in the current unit speed data acquisition cycle is acquired, where the unit speed data is expressed as the number of rotations of the main shaft of the pumped storage device per unit time; Step S1-2: Select the unique identifier of the pumped storage equipment as the primary key, and store the unit speed data corresponding to the timestamp as the value to construct a first set of equipment status analysis; Step S1-3: Acquire the unit speed data of the pumped storage equipment during the data acquisition period through the magnetoresistive speed sensor, and construct a second set of real-time equipment status analysis according to the storage method of step S1-2.

3. The method for real-time evaluation of pumped storage equipment status based on data analysis according to claim 2, characterized in that: The specific steps of step S2 are as follows: Step S2-1, traversing and reading the unit speed data in the first set of device state analysis, calculating the absolute value of the difference between two sets of unit speed data at adjacent moments in the first set of device state analysis, and selecting the maximum absolute value of the pumped storage device unit speed through a bubble sort algorithm, recording it as the comprehensive unit speed fluctuation peak value. The comprehensive unit speed fluctuation peak value is represented by the maximum instantaneous fluctuation of the number of revolutions of the main shaft of the pumped storage device unit per unit time between two adjacent sampling moments during the operation of the unit; Step S2-2, calculating the average value of the unit speed data in the first set of equipment status analysis, and recording it as the first unit speed average value; Calculate the average value of the unit speed data in the second set of real-time equipment status analysis, and record it as the second unit speed average value; Step S2-3: Obtain the standard unit speed of the pumped storage equipment within the current unit speed data collection period through weighted fusion calculation based on the average value of the first unit speed and the average value of the second unit speed.

4. A method for real-time assessment of pumped storage equipment status based on data analysis according to claim 3, characterized in that: The specific steps of step S3 are as follows: Step S3-1: Select the unique identifier of any pumped-storage equipment within the current unit speed data collection period as an index, extract the historical unit speed data of the corresponding pumped-storage equipment from the first device status analysis set using the index, and construct a single-unit speed analysis set according to the storage method of step S1-2. The single-unit speed analysis set is specifically an independent data set established for each pumped-storage equipment. The set uses the device unique identifier as the primary key index, and associates and stores all unit speed data within each unit speed data collection period to form a one-to-one mapping time series data structure. Step S3-2: using a time series prediction model through a single unit speed analysis set to predict the speed change trend of the pumped storage equipment; Step S3-3, traverse and read the unit speed data in the single unit speed analysis set, calculate the absolute value of the difference between the two sets of unit speed data at adjacent moments, and use it as the maximum value of the single unit speed fluctuation of the pumped storage equipment, which is recorded as the single unit speed fluctuation peak value.

5. The method for real-time assessment of pumped storage equipment status based on data analysis according to claim 4, characterized in that: The specific steps of step S4 are as follows: Step S4-1, calculating the average speed of the pumped storage equipment based on the predicted speed change trend of the unit to obtain the average speed of the unit; Step S4-2: Utilize the comprehensive unit speed fluctuation peak value and the single unit speed fluctuation peak value to obtain the standard unit speed fluctuation peak value of the pumped storage equipment according to weighted fusion calculation. The standard unit speed fluctuation peak value is represented by the instantaneous maximum number of rotations of the unit main shaft per unit time after the pumped storage equipment is affected by negative fluctuation factors during operation.

6. The method for real-time assessment of pumped storage equipment status based on data analysis according to claim 5, characterized in that: In step S4, it also includes: Step S4-3: Calculate an upper limit of the unit speed by adding the average unit speed of the pumped storage equipment to the peak value of the standard unit speed fluctuation. The upper limit of the unit speed represents the maximum limit value that the unit speed of the pumped storage equipment is allowed to reach under safe operating conditions. Step S4-4: Monitor the pumped storage equipment using the upper limit of the unit speed and the standard unit speed, and perform data analysis and processing on the monitoring results to form a unit speed analysis set. The specific process of the data analysis and processing is as follows: Step S4-4-1, using the upper limit value of the unit speed of the pumped storage equipment minus the standard unit speed, performing absolute value processing on the obtained difference to obtain the absolute value deviation of the upper limit of the unit speed from the standard value; Step S4-4-2: Select the timestamp data of the pumped storage equipment as the primary key, select the absolute deviation of the upper limit of the unit speed from the standard value as the value, and store it after time series arrangement to construct a unit speed analysis set.

7. The method for real-time assessment of pumped storage equipment status based on data analysis according to claim 6, characterized in that: The specific steps of step S5 are as follows: Step S5-1, traverse and read the absolute deviation of the upper limit of the unit speed from the standard value in the group speed analysis set, and input it into the time series prediction model in turn to analyze and predict the change trend of the unit speed of the pumped storage equipment; Step S5-2: using the data analysis process from step S3 to step S4, obtaining the speed change trend of each pumped storage device within the current speed data collection period; Step S5-3: extract the unit speed value corresponding to the maximum value of the horizontal coordinate in the speed change trend of the pumped storage equipment, compare the extracted unit speed value with the upper limit of the unit speed, and evaluate and warn the pumped storage equipment based on the comparison and judgment result. The specific process of the comparison and judgment is as follows: Step S5-3-1: When the speed of the pumped storage equipment exceeds the upper limit of the speed, it is determined that the speed of the equipment is abnormal and an early warning signal is issued; Step S5-3-2: When the speed value of the pumped storage equipment does not exceed the upper limit of the speed of the unit, it is determined that the speed of the unit is normal, no warning signal is issued, and the speed of the unit is continuously monitored.

8. A real-time assessment system for the status of a pumped-storage power plant based on data analysis, applied to the real-time assessment method for the status of a pumped-storage power plant based on data analysis according to any one of claims 1 to 7, characterized in that: The real-time evaluation system for the status of pumped storage equipment includes a data acquisition module, a data processing module, a stand-alone analysis module, a threshold monitoring module and an evaluation and early warning module; The data acquisition module is used to obtain historical and real-time unit speed data of the pumped storage equipment and construct a collection; the data processing module is used to calculate and analyze the collected historical and real-time data and generate a standard unit speed; the single-machine analysis module is used to predict the speed trend and analyze the fluctuation characteristics based on the historical data of the single machine; The threshold monitoring module is used to combine the speed mean and peak computer group safe operation thresholds and analyze deviations; the evaluation and warning module is used to predict future trends based on deviation data and trigger abnormal warnings; The output end of the data acquisition module is electrically connected to the input end of the data processing module; the output end of the data processing module is electrically connected to the input end of the stand-alone analysis module; the output end of the stand-alone analysis module is electrically connected to the input end of the threshold monitoring module; the output end of the threshold monitoring module is electrically connected to the input end of the evaluation and early warning module.

9. The real-time evaluation system for pumped storage equipment status based on data analysis according to claim 8, characterized in that: The data acquisition module includes a historical data acquisition unit and a real-time data acquisition unit; the historical data acquisition unit is used to obtain the historical unit speed data of the pumped storage equipment through the PLC control system and the OPC single unit speed fluctuation peak UA protocol; the real-time data acquisition unit is used to obtain the real-time unit speed data of the pumped storage equipment in the current cycle through the magnetoresistive speed sensor; The data processing module includes a peak calculation unit and a mean fusion unit; the peak calculation unit is used to traverse historical data and calculate the peak value of the comprehensive unit speed fluctuation of the pumped storage equipment through a bubble sort algorithm; the mean fusion unit is used to calculate the average value of historical and real-time data and generate a standard unit speed through weighted fusion; The single-machine analysis module includes a trend prediction unit and a fluctuation analysis unit; the trend prediction unit is used to predict the speed change trend of the pumped storage equipment through a time series model; The fluctuation analysis unit is used to calculate the absolute value of the speed difference between adjacent moments of a single unit and extract the peak value of the speed fluctuation of a single unit.

10. The real-time evaluation system for pumped storage equipment status based on data analysis according to claim 8, characterized in that: The threshold monitoring module includes a threshold calculation unit and a deviation analysis unit; the threshold calculation unit is used to calculate the upper limit of safe operation of the pumped storage equipment by combining the average speed of the unit and the standard peak value; The deviation analysis unit is used to compare the upper speed limit with the standard speed, and calculate the deviation to store and construct an analysis set; The evaluation and warning module includes a trend prediction unit and a warning triggering unit; The trend prediction unit is used to predict the future speed change trend of the pumped storage equipment based on historical deviation data; the early warning trigger unit is used to compare the real-time speed with the upper limit value, judge the unit status and trigger abnormal early warning or continuous monitoring.

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