Intelligent measurement method and device for net water head or net lift of reversible hydraulic turbine based on multi-source sensor fusion and digital twinning, electronic equipment and storage medium

Abstract

The application provides an intelligent measuring method and device for net water head or net lift of a reversible hydraulic turbine based on multi-source sensor fusion and digital twinning, an electronic device and a storage medium. The application realizes high-precision and real-time dynamic measurement, significantly improves the operation efficiency of the unit, and is suitable for the optimized operation and predictive maintenance of pumped storage power stations and conventional hydropower stations.

Description

Technical Field

[0001] This invention relates to the field of hydropower technology, specifically to a high-precision measurement method, device, electronic equipment, and storage medium for net head or net lift of a reversible pump-turbine under both turbine and pump operating conditions. Background Technology

[0002] The net head or net lift of a reversible hydro turbine is a key parameter characterizing the unit's work capacity, defined as the total unit energy difference between the high-pressure and low-pressure reference sections of the turbine. This parameter directly affects the unit's output power, input power, operating efficiency, and stability. Current standards typically include three components in the calculation of net head or net lift: the pressure potential energy difference between the high-pressure and low-pressure reference sections, the elevation difference between the reference sections, and the kinetic energy difference at the sections.

[0003] In the current actual operation of power plants, the methods for obtaining net head / net lift are mainly divided into three categories, and each method has obvious technical shortcomings, as detailed below: Firstly, the single differential pressure sensor measurement method. Currently, the net head and net lift data used in the unit speed control system are mostly taken directly from differential pressure sensors installed at the high and low pressure reference sections. This measurement method has several drawbacks: First, the measurement accuracy is limited. The differential pressure sensor itself not only has a large measurement error, but is also easily affected by on-site electromagnetic interference, pressure tap blockage, residual air bubbles in the pipe, and other on-site operating conditions, with actual measurement errors generally exceeding 3%. Second, the measurement dimensions are incomplete. This method cannot capture the fluid kinetic energy difference between sections, resulting in missing calculation results for net head and net lift. Third, the dynamic response performance is poor. The sensor signal has a significant lag, making it impossible to track rapid dynamic changes in head and lift in real time, making it difficult for the speed control system to achieve precise dynamic regulation. Measurement deviations in head and lift will directly cause inaccurate guide vane opening control, causing the reversible unit to deviate from the optimal design conditions when operating under turbine opening conditions and pump coordinated operation conditions. This not only significantly reduces the unit's operating efficiency but also easily leads to problems such as unit vibration and excessive swing, shortening the equipment's service life.

[0004] Secondly, the upstream and downstream water level difference method. Some power stations use the water level difference (i.e., gross head) measured by water level sensors in the upstream and downstream reservoirs directly as the net head / lift. This method ignores the head loss of the water conveyance system and is only suitable for power stations with extremely short water diversion systems and negligible head losses. For conventional hydropower stations or pumped storage power stations with long water diversion systems (L>300m), frictional losses along the route and local head losses can reach several meters or even tens of meters, and simply using the gross head will introduce serious errors.

[0005] Third, the fixed head loss correction method. To compensate for the shortcomings of the water level difference method, a fixed empirical head loss value is estimated by subtracting or adding the upstream and downstream water level difference. However, the head loss of an actual system is not a fixed constant, but changes dynamically in real time according to parameters such as the number of operating units, flow rate through the unit, and unit output. Moreover, the loss amplitude varies significantly when operating conditions fluctuate. The fixed empirical correction value cannot adapt to the dynamic changes in head loss, and will produce large calculation deviations under different operating conditions, making it difficult to meet the requirements of high-precision and refined operation control of the unit.

[0006] In summary, the existing technology lacks a reversible turbine net head / net lift measurement method that can simultaneously achieve high precision, real-time dynamic response, and adaptability to long-distance water conveyance systems and variable operating conditions. Summary of the Invention

[0007] To address the problems of low accuracy in measuring net head / net lift in existing technologies, poor dynamic response due to differential pressure sensors' inability to track changes in operating conditions in real time, and inability to adapt to long-distance water transmission systems and variable operating conditions, this invention proposes an intelligent measurement method for the net head or net lift of reversible water turbines based on multi-source sensor fusion and digital twins. The method includes: Step 1: Use multi-source sensors to acquire water level data, flow rate data, and pressure data; then compare the acquired data comprehensively, remove outliers, and output high-confidence data; Step 2: Based on the topology of the water conveyance system, and according to the number of reversible turbines in operation and their operating conditions in the same water conveyance system, construct a dynamic head loss digital twin calculation model. Step 3: Input the flow rate data from the high-confidence data into the dynamic head loss digital twin calculation model to obtain the dynamic head loss value. Then, use the water level data from the high-confidence data and the dynamic head loss value to calculate the real-time net head. Or real-time net head ; Step 4: Using the pressure and flow data from the high-confidence dataset, calculate the net head of the reversible turbine based on Bernoulli's equation. Or net head ; Step 5: Connect the real-time water purification heads respectively With water purifier Real-time net head With net head Perform comprehensive comparative dynamic calibration to determine the final water purification head. Or final net head ; Step Six: Connect the final purified water head Or final net head Connect to the unit speed control system, adjust the guide vane opening and unit speed to achieve free matching between the net water head and power or the net head and input. Step 7: Based on real-time operating data, generate head-flow-output curves or head-flow-input curves, compare them with model test data, reverse-correct parameters of each stage, and generate the final head-flow-output curves or head-flow-input curves and efficiency evaluation reports.

[0008] Furthermore, in step one, Specifically, water level data is obtained by using water level sensors to collect the water level of the upper reservoir. and the water level of the lower reservoir ; Specifically, the flow rate data is obtained by using an electromagnetic flowmeter to collect the turbine operating flow rate of the reversible turbine. and water pump operating flow rate , Specifically, pressure data is obtained by using a differential pressure sensor to collect the pressure potential energy difference between the high-pressure and low-pressure reference sections under turbine operating conditions. Pressure potential energy difference at high-pressure and low-pressure reference sections during water pump operation .

[0009] Furthermore, After acquiring water level data, the accuracy of the collected water level signal is determined by filtering, delaying, and then checking the rate of change and abrupt change. At the same time, it is compared with the measured value on the water level measuring scale to ensure the accuracy of the data.

[0010] Furthermore, in step three, Under turbine operating conditions, the dynamic head loss is:

[0011] Under pump operating conditions, the dynamic head loss is:

[0012] Where i represents the number of operating units.

[0013] Furthermore, in step three, Real-time water purification head The calculation method is as follows:

[0014] in, This refers to the dynamic head loss under turbine operating conditions. Real-time net head The calculation method is as follows:

[0015] in, This refers to the dynamic head loss under pump operating conditions.

[0016] Furthermore, in step four, Water Purifier Head The calculation method is as follows:

[0017] in, The specific gravity of water; The elevation difference between the high-pressure and low-pressure reference sections; It is the acceleration due to gravity; This represents the area of ​​the high-pressure reference section; The area of ​​the low-pressure reference section; , The velocity uniformity coefficient; This refers to the operating flow rate of the water turbine.

[0018] Furthermore, in step four, Net head The calculation method is as follows:

[0019] in, This refers to the operating flow rate of the water pump.

[0020] This invention proposes an intelligent measurement device for the net head or net lift of a reversible water turbine based on multi-source sensor fusion and digital twin, comprising: Data acquisition module: Uses multi-source sensors to acquire water level data, flow rate data, and pressure data; and compares the acquired data comprehensively, removes outliers, and outputs high-confidence data; Digital twin model construction module: Based on the topology of the water conveyance system, and according to the number of reversible turbines in operation and their operating conditions in the same water conveyance system, a dynamic head loss digital twin calculation model is constructed. The first calculation module: It uses the flow rate data from the high-confidence data set as input into the dynamic head loss digital twin calculation model to obtain the dynamic head loss value. Then, it uses the water level data from the high-confidence data set and the dynamic head loss value to calculate the real-time net head. Or real-time net head ; The second calculation module: using pressure and flow data from the high-confidence dataset, calculates the net head of the reversible turbine based on Bernoulli's equation. Or net head ; Dynamic calibration module: This module adjusts the real-time water purification head... With water purifier Real-time net head With net head Perform comprehensive comparative dynamic calibration to determine the final water purification head. Or final net head ; Control module: This will control the final purified water head. Or final net head Connect to the unit speed control system, adjust the guide vane opening and unit speed to achieve free matching between net water head and power or net head and input. Curve generation and correction module: Based on real-time operating data, it generates head-flow-output curves or head-flow-input curves, compares them with model test data, reverse corrects the parameters of each link, and generates the final head-flow-output curve or head-flow-input curve and efficiency evaluation report.

[0021] The present invention proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0022] The present invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the above-described method.

[0023] The beneficial effects of this invention are: To address the problems of low accuracy in measuring net head / net lift, poor dynamic response, and inability to adapt to long-distance water conveyance systems and variable operating conditions in existing technologies, this invention proposes an intelligent measurement method, device, electronic equipment, and storage medium for reversible turbine net head or net lift based on multi-source sensor fusion and digital twins, which has the following improvements: 1. By using multi-source sensors to collaboratively acquire and fuse data, outliers are eliminated, and a high-confidence dataset is output, significantly improving the accuracy of the original data. Furthermore, by combining dynamic calibration of the energy conservation path and the pressure potential energy path, the system error and kinetic energy difference of a single sensor are effectively compensated.

[0024] 2. Based on a digital twin model, dynamic head / lift loss is calculated in real time. This model can correct the loss coefficient online according to the number of operating units and the flow rate through the unit, and output the net head / lift under the current operating conditions in real time, thus avoiding the defects of the fixed loss method.

[0025] 3. This invention does not rely on the simplified assumption of upstream and downstream water level difference, but accurately calculates the loss through the topology of the water conveyance system and the dynamic head loss model. Therefore, it is applicable to power plants with water conveyance systems of any length, including long water conveyance systems with L>300m, and supports multi-unit parallel operation scenarios, with significantly enhanced generalization ability.

[0026] 4. This invention integrates the final clean water head / lift into the speed control system in real time, automatically adjusting the guide vane opening and unit speed to achieve optimal matching of head / lift and power / input, thereby improving power generation efficiency. At the same time, by comparing real-time operating data with model test data, the parameters of the digital twin model are reverse-corrected to generate real-time characteristic curves and efficiency evaluation reports, providing a basis for predictive maintenance. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of the overall process of the method of the present invention; Figure 2 This is a schematic diagram illustrating the measurement of head / lift using Bernoulli's equation for pressure potential energy. Detailed Implementation

[0029] 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.

[0030] Combination Figures 1-2 This invention proposes an intelligent measurement method for the net head or net lift of a reversible water turbine based on multi-source sensor fusion and digital twin, the method comprising: Step 1: Use multi-source sensors to acquire water level data, flow rate data, and pressure data; then compare the acquired data comprehensively, remove outliers, and output high-confidence data; Furthermore, in step one, Specifically, water level data is obtained by using water level sensors to collect the water level of the upper reservoir. and the water level of the lower reservoir ; Specifically, the flow rate data is obtained by using an electromagnetic flowmeter to collect the turbine operating flow rate of the reversible turbine. and water pump operating flow rate , Specifically, pressure data is obtained by using a differential pressure sensor to collect the pressure potential energy difference between the high-pressure and low-pressure reference sections under turbine operating conditions. Pressure potential energy difference at high-pressure and low-pressure reference sections during water pump operation .

[0031] Furthermore, After acquiring water level data, the accuracy of the collected water level signal is determined by filtering, delaying, and then checking the rate of change and abrupt change. At the same time, it is compared with the measured value on the water level measuring scale to ensure the accuracy of the data.

[0032] Specifically, this is achieved by installing water level sensors and water level gauges. Water level sensors and water level measuring gauges are installed in both the upper and lower reservoirs of the power station to collect real-time data on the water level in the upper reservoir. and the water level of the lower reservoir The accuracy of the collected water level signal is determined by filtering, delay, and change rate and abrupt change. It can also be compared with the measured value on the water level measuring scale to ensure the accuracy of the collected data.

[0033] Install an electromagnetic flow meter. At an appropriate location on the intake pipe before the turbine casing inlet, install the electromagnetic flow meter to measure the flow rate through the turbine. and .

[0034] Differential pressure sensors are installed. Pressure measuring points are arranged at the turbine spiral casing inlet (high-pressure reference measuring section) and the tailrace outlet (low-pressure reference measuring section). Differential pressure sensors are installed at these measuring sections, one as the main sensor and one as a backup, to monitor the pressure potential energy difference between the high-pressure and low-pressure sections of the turbine. and .

[0035] Then, the water level data acquired synchronously from multiple sensors was obtained. and ,flow and ,pressure and The data is comprehensively compared, outliers (such as sensor malfunction data) are removed, and high-confidence data is output. The measured data must cover all operating heads / lifts of the turbine and all operating load ranges specified in the documentation.

[0036] Step 2: Based on the topology of the water conveyance system, and according to the number of reversible turbines in operation and their operating conditions in the same water conveyance system, construct a dynamic head loss digital twin calculation model. Step 3: Input the flow rate data from the high-confidence data into the dynamic head loss digital twin calculation model to obtain the dynamic head loss value. Then, use the water level data from the high-confidence data and the dynamic head loss value to calculate the real-time net head. Or real-time net head ; Furthermore, in step three, Under turbine operating conditions, the dynamic head loss is:

[0037] Under pump operating conditions, the dynamic head loss is:

[0038] Where i represents the number of operating units.

[0039] Furthermore, in step three, Real-time water purification head The calculation method is as follows:

[0040] in, This refers to the dynamic head loss under turbine operating conditions. Real-time net head The calculation method is as follows:

[0041] in, This refers to the dynamic head loss under pump operating conditions.

[0042] Step 4: Using the pressure and flow data from the high-confidence dataset, calculate the net head of the reversible turbine based on Bernoulli's equation. Or net head ; Furthermore, in step four, Water Purifier Head The calculation method is as follows:

[0043] in, The specific gravity of water; The elevation difference between the high-pressure and low-pressure reference sections; It is the acceleration due to gravity; This represents the area of ​​the high-pressure reference section; The area of ​​the low-pressure reference section; , The velocity uniformity coefficient; This refers to the operating flow rate of the water turbine.

[0044] Furthermore, in step four, Net head The calculation method is as follows:

[0045] in, This refers to the operating flow rate of the water pump.

[0046] Step four specifically involves: updating the turbine's operating conditions in real time, running the digital twin model, and calculating the theoretical net head. / Yangcheng That is, using the measured flow rate value. and The dynamic head loss value is obtained. and Then substitute it into the formula:

[0047]

[0048] The real-time dynamic head of the reversible turbine can then be obtained. / Yangcheng .

[0049] Then, the net head is calculated using Bernoulli's equation pressure potential energy path. / Yangcheng The head / lift is composed of three parts: position head, pressure head, and velocity head. The obtained flow rate is then used... and ,pressure and Numerical values ​​are used to determine the net head of the reversible water turbine. / Yangcheng Numerical value. The derived calculation formula is as follows:

[0050] in, For clean water head / lift; , Elevation installation for gauges at the high-pressure and low-pressure reference measurement sections of the water turbine; , Pressure gauges at high-pressure and low-pressure reference measurement sections of the water turbine; , The average flow velocity at the high-pressure and low-pressure reference measurement sections of the water turbine; , The velocity uniformity coefficient is approximately taken as 1; When connecting a differential pressure sensor, ; The specific gravity of water; The pressure difference is recorded at the high-pressure and low-pressure reference measurement sections of the water turbine. The turbine flow rate; , The cross-sectional area of ​​the high-pressure and low-pressure reference measurements for the water turbine.

[0051] Water Purifier Head The calculation method is as follows:

[0052] in, This refers to the operating flow rate of the water turbine.

[0053] Net head The calculation method is as follows:

[0054] in, This refers to the operating flow rate of the water pump.

[0055] Step 5: Connect the real-time water purification heads respectively With water purifier Real-time net head With net head Perform comprehensive comparative dynamic calibration to determine the final water purification head. Or final net head ; Step Six: Connect the final purified water head Or final net head Connect to the unit speed control system, adjust the guide vane opening and unit speed to achieve free matching between net water head and power or net head and input. Step six specifically involves adjusting the final purified water head... Or final net head Connect to the unit speed control system to automatically adjust the guide vane opening and unit speed to achieve the desired water head. / Yangcheng With power / input force Flexible matching improves power generation efficiency.

[0056] Step 7: Based on real-time operating data, generate head-flow-output curves or head-flow-input curves, compare them with model test data, reverse-correct parameters of each stage, and generate the final head-flow-output curves or head-flow-input curves and efficiency evaluation reports.

[0057] This invention proposes an intelligent measurement device for the net head or net lift of a reversible water turbine based on multi-source sensor fusion and digital twin, comprising: Data acquisition module: Uses multi-source sensors to acquire water level data, flow rate data, and pressure data; and compares the acquired data comprehensively, removes outliers, and outputs high-confidence data; Digital twin model construction module: Based on the topology of the water conveyance system, and according to the number of reversible turbines in operation and their operating conditions in the same water conveyance system, a dynamic head loss digital twin calculation model is constructed. The first calculation module: It uses the flow rate data from the high-confidence data set as input into the dynamic head loss digital twin calculation model to obtain the dynamic head loss value. Then, it uses the water level data from the high-confidence data set and the dynamic head loss value to calculate the real-time net head. Or real-time net head ; The second calculation module: using pressure and flow data from the high-confidence dataset, calculates the net head of the reversible turbine based on Bernoulli's equation. Or net head ; Dynamic calibration module: This module adjusts the real-time water purification head... With water purifier Real-time net head With net head Perform comprehensive comparative dynamic calibration to determine the final water purification head. Or final net head ; Control module: This will control the final purified water head. Or final net head Connect to the unit speed control system, adjust the guide vane opening and unit speed to achieve free matching between net water head and power or net head and input. Curve generation and correction module: Based on real-time operating data, it generates head-flow-output curves or head-flow-input curves, compares them with model test data, reverse corrects the parameters of each link, and generates the final head-flow-output curve or head-flow-input curve and efficiency evaluation report.

[0058] The present invention proposes an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0059] The present invention proposes a computer-readable storage medium for storing computer instructions, which, when executed by a processor, implement the steps of the above-described method.

[0060] This invention discloses an intelligent measurement system and method for the head of a hydroelectric turbine based on sensor fusion and digital twin. The system collects pressure, flow, and water level data through multi-source sensor modules, fuses the data, and inputs it into a digital twin module for multiphysics simulation. The model parameters are then calibrated using measured data, ultimately outputting high-precision head measurement results and equipment health status assessment. This method constructs a closed loop of "sensing, transmission, calculation, and control," solving the problems of large measurement errors and response lag in traditional methods. It can significantly improve the operating efficiency and equipment reliability of hydroelectric power stations and is applicable to the optimized scheduling and predictive maintenance of pumped storage and conventional hydroelectric power stations.

[0061] The technical solution of this invention patent is as follows: A high-confidence dataset is constructed by collaboratively collecting data from multiple sensors, including water level, flow rate, and pressure. Based on the physical characteristics of the water conveyance system, a dynamic mapping relationship is established between head loss and the number of generating units and flow rate, enabling real-time calculation of head loss. Data dynamic calibration is achieved through cross-validation using the energy conservation method and the pressure potential energy method, and the results are fed back to the speed control system, forming a "measurement-control-optimization" closed loop. Finally, the real-time operating data is compared with model test data to generate the final real-time curve of head / lift-flow rate-output and an efficiency evaluation report.

[0062] The above provides a detailed description of the intelligent measurement method, device, electronic equipment, and storage medium for the net head or net lift of a reversible water turbine based on multi-source sensor fusion and digital twin proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. An intelligent measurement method for the net head or net lift of a reversible water turbine based on multi-source sensor fusion and digital twin, characterized in that, Includes the following steps: Step 1: Use multi-source sensors to acquire water level data, flow rate data, and pressure data; then compare the acquired data comprehensively, remove outliers, and output high-confidence data; Step 2: Based on the topology of the water conveyance system, and according to the number of reversible turbines in operation and their operating conditions in the same water conveyance system, construct a dynamic head loss digital twin calculation model. Step 3: Input the flow rate data from the high-confidence data into the dynamic head loss digital twin calculation model to obtain the dynamic head loss value. Then, use the water level data from the high-confidence data and the dynamic head loss value to calculate the real-time net head. Or real-time net head ; Step 4: Using the pressure and flow data from the high-confidence dataset, calculate the net head of the reversible turbine based on Bernoulli's equation. Or net head ; Step 5: Connect the real-time water purification heads respectively With water purifier Real-time net head With net head Perform comprehensive comparative dynamic calibration to determine the final water purification head. Or final net head ; Step Six: Connect the final purified water head Or final net head Connect to the unit speed control system, adjust the guide vane opening and unit speed to achieve free matching between net water head and power or net head and input. Step 7: Based on real-time operating data, generate head-flow-output curves or head-flow-input curves, compare them with model test data, reverse-correct parameters of each stage, and generate the final head-flow-output curves or head-flow-input curves and efficiency evaluation reports.

2. The method according to claim 1, characterized in that, In step one, Specifically, water level data is obtained by using water level sensors to collect the water level of the upper reservoir. and the water level of the lower reservoir ; Specifically, the flow rate data is obtained by using an electromagnetic flowmeter to collect the turbine operating flow rate of the reversible turbine. and water pump operating flow rate ; Specifically, pressure data is obtained by using a differential pressure sensor to collect the pressure potential energy difference between the high-pressure and low-pressure reference sections under turbine operating conditions. Pressure potential energy difference at high-pressure and low-pressure reference sections during water pump operation .

3. The method according to claim 2, characterized in that, After acquiring water level data, the accuracy of the collected water level signal is determined by filtering, delaying, and then checking the rate of change and abrupt change. At the same time, it is compared with the measured value on the water level measuring scale to ensure the accuracy of the data.

4. The method according to claim 1, characterized in that, In step three, Under turbine operating conditions, the dynamic head loss is: Under pump operating conditions, the dynamic head loss is: Where i represents the number of operating units.

5. The method according to claim 1, characterized in that, In step three, Real-time water purification head The calculation method is as follows: in, This refers to the dynamic head loss under turbine operating conditions. Real-time net head The calculation method is as follows: in, This refers to the dynamic head loss under pump operating conditions.

6. The method according to claim 1, characterized in that, In step four, Water Purifier Head The calculation method is as follows: in, The specific gravity of water; The elevation difference between the high-pressure and low-pressure reference sections; It is the acceleration due to gravity; This represents the area of ​​the high-pressure reference section; The area of ​​the low-pressure reference section; , The velocity uniformity coefficient; This refers to the operating flow rate of the water turbine.

7. The method according to claim 1, characterized in that, In step four, Net head The calculation method is as follows: in, This refers to the operating flow rate of the water pump.

8. An intelligent measurement device for the net head or net lift of a reversible water turbine based on multi-source sensor fusion and digital twin, characterized in that, include: Data acquisition module: Uses multi-source sensors to acquire water level data, flow rate data, and pressure data; The acquired data is then comprehensively compared, outliers are removed, and high-confidence data is output. Digital twin model construction module: Based on the topology of the water conveyance system, and according to the number of reversible turbines in operation and their operating conditions in the same water conveyance system, a dynamic head loss digital twin calculation model is constructed. The first calculation module: It uses the flow rate data from the high-confidence data set as input into the dynamic head loss digital twin calculation model to obtain the dynamic head loss value. Then, it uses the water level data from the high-confidence data set and the dynamic head loss value to calculate the real-time net head. Or real-time net head ; The second calculation module: using pressure and flow data from the high-confidence dataset, calculates the net head of the reversible turbine based on Bernoulli's equation. Or net head ; Dynamic calibration module: This module adjusts the real-time water purification head... With water purifier Real-time net head With net head Perform comprehensive comparative dynamic calibration to determine the final water purification head. Or final net head ; Control module: This will control the final purified water head. Or final net head Connect to the unit speed control system, adjust the guide vane opening and unit speed to achieve free matching between net water head and power or net head and input. Curve generation and correction module: Based on real-time operating data, it generates head-flow-output curves or head-flow-input curves, compares them with model test data, reverse corrects the parameters of each link, and generates the final head-flow-output curve or head-flow-input curve and efficiency evaluation report.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium for storing computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-7.

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