A method, system and program product for controlling the active air supply of a hydraulic turbine at low loads

Abstract

This invention relates to the field of hydro-turbine technology and discloses a method, system, and program product for active air replenishment control of hydro-turbines under low load conditions. The method includes: acquiring a multi-condition test dataset, a set of actual turbine parameters, a set of model turbine parameters, and a set of real-time operating parameters of the hydro-turbine under the current low load condition; determining the optimal air replenishment amount for the model turbine under multiple low load test conditions based on the actual turbine parameters and the model turbine parameters; determining the initial air replenishment amount relationship by using regression analysis based on the multi-condition test dataset, the actual turbine parameters, and the optimal air replenishment amounts; calculating the first air replenishment amount of the hydro-turbine under the current low load condition based on the initial air replenishment amount relationship using the real-time operating parameter set; and controlling an electromagnetic control valve to replenish air to the hydro-turbine using a programmable PLC controller based on the first air replenishment amount, thereby realizing active air replenishment control of the hydro-turbine under low load conditions based on real-time operating conditions.

Description

Technical Field

[0001] This invention relates to the field of water turbine technology, specifically to a method, system, and program product for controlling the active air supply volume of a water turbine under low load. Background Technology

[0002] In new power systems, the role of hydropower units is shifting from stable power supply to flexible operation, necessitating a further expansion of their flexible operating range from the current 45%-100%. However, the wide operating range of hydropower units is limited by the inability to adjust the turbine runner blades. When operating outside of optimal conditions, cavitation, vibration, and sway caused by turbulence at the turbine runner inlet and outlet affect the stable operation of the unit.

[0003] Currently, the primary methods for air injection in hydropower units are natural air injection through the shaft center hole or forced air injection through the turbine top cover, mainly for the tailrace vortex condition within the 45%-100% load range. Natural air injection is mainly used to eliminate cavitation at the runner outlet and tailrace inlet, but this method can only achieve automatic opening of the air injection valve under vacuum suction when a certain level is reached, allowing outside air to directly enter the lower chamber of the runner through the shaft center hole, thereby reducing unit vibration and noise. Therefore, to meet the wide-load operation requirements on site, it is necessary to study a more effective forced air injection method for the low load range of 0-45%.

[0004] However, existing research on forced air supply systems on the generator top cover primarily addresses specific operating conditions. The opening and closing of the air supply valves are typically controlled by a fixed value. When the vacuum level weakens to a certain extent, the air supply valves often become inflexible, failing to open and close promptly, leading to severe unit vibration and backflow. Since the required stable air supply volume varies depending on the operating conditions, it is necessary to research more rational methods for controlling the air supply volume based on actual on-site operating conditions, thereby providing an effective basis for the stability control of the generator units in operation. Summary of the Invention

[0005] This invention provides a method, system, and program product for controlling the active air supply volume of a water turbine under low load, in order to solve the problems of existing air supply valves, which are usually controlled by a certain value and cannot be opened and closed in a timely manner, and cannot be combined with the actual operating conditions on site to control the air supply volume, thus causing severe vibration of the unit and backflow.

[0006] In a first aspect, the present invention provides a method for controlling the active air supply volume of a hydro turbine under low load, used in a hydro turbine active air supply volume control system, the system being connected to the hydro turbine, the system including a programmable PLC controller and an electromagnetic control valve; the method includes: The process involves acquiring a multi-condition test dataset, a set of parameters for the actual turbine, a set of parameters for the model turbine, and a set of real-time operating parameters for the turbine under the current low-load condition. Based on the set of parameters for the actual turbine and the model turbine, the optimal air supply volume for the model turbine under multiple low-load test conditions is determined. Using the multi-condition test dataset, the set of parameters for the actual turbine, and the optimal air supply volume for multiple conditions, an initial air supply volume formula is determined through regression analysis. Based on the real-time operating parameters, the first air supply volume for the turbine under the current low-load condition is calculated using the initial air supply volume formula. Based on the first air supply volume, an electromagnetic control valve is used to supply air to the turbine via a programmable PLC controller.

[0007] The present invention provides a method for controlling the active air supply volume of a turbine under low load. By combining the parameter sets of the actual turbine and the parameter sets of the model turbine, the optimal air supply volume for the model turbine under multiple low load test conditions is determined. This method achieves the acquisition of an air supply volume adapted to low load conditions using model turbine experiments, providing a reliable basis for establishing the subsequent air supply volume formula for the actual turbine. Furthermore, by determining the initial air supply volume relationship through regression analysis, a calculation formula for the air supply volume adapted to the turbine's operating conditions is constructed, achieving a correlation and matching between the air supply volume and the operating conditions, overcoming the limitations of fixed-value air supply. Furthermore, by calculating the first air supply volume under the current low load condition, the required air supply volume can be accurately calculated based on real-time operating conditions, achieving dynamic matching of the air supply volume according to the operating conditions. Finally, a programmable PLC controller controls the electromagnetic control valve to supply air to the turbine, converting the calculated air supply volume into actual air supply actions, achieving precise execution and adjustment of the air supply volume. Therefore, by implementing this invention, active air replenishment control based on real-time operating conditions is realized under low-load conditions of the turbine, overcoming the shortcomings of traditional fixed-value air replenishment. This allows the air replenishment volume to be adapted to the real-time low-load operating conditions, improving the accuracy of low-load air replenishment of the turbine and contributing to the stable operation of the unit under low load.

[0008] In one optional implementation, based on the actual turbine parameter set and the model unit parameter set, the optimal air injection rate for the turbine under multiple low-load test conditions is determined, including: Based on the parameter sets of the actual turbine and the parameter sets of the model units, multiple head values ​​and optimal flow rates of the model units were calculated using a similarity conversion method. Based on the optimal flow rates of the model units, multiple low-load test conditions of the turbine model units were determined. Based on the head values ​​of the multiple model units, the air supply volume of the turbine model units was tested under multiple low-load test conditions, and the optimal air supply volume values ​​for multiple conditions were determined.

[0009] The present invention provides a method for controlling the active air supply volume of a turbine under low load. Through a similarity conversion method, it obtains the head and optimal flow rate values ​​of the model unit, achieving accurate conversion of real-machine parameters to the model unit. This ensures consistency between model tests and real-machine operating conditions, allowing model test results to be effectively transferred to the real unit. Furthermore, by determining the low-load test conditions of the model unit, the low-load test range of the model unit is precisely defined, ensuring that the test conditions cover the actual low-load operating scenarios of the turbine. Moreover, by determining the optimal air supply volume through model unit air supply volume testing, the optimal air supply volume under various low-load conditions of the model unit can be obtained, providing accurate and effective test data for establishing the initial air supply volume relationship for the real unit. Therefore, by implementing this invention, through similarity conversion and targeted tests of the model unit, it is possible to accurately obtain basic air supply volume data adapted to the low-load operating conditions of the real unit, thereby ensuring a high degree of matching between the subsequently established air supply volume relationship and the actual operating conditions of the real unit, contributing to improving the scientific rigor and reliability of air supply volume calculations.

[0010] In one optional implementation, based on a multi-condition test dataset, a real machine parameter set, and optimal air injection rates for multiple conditions, an initial air injection rate relationship is determined through regression analysis, including: Based on the multi-condition test dataset and the actual machine parameter set, multiple flow deviation values ​​and multiple head deviation values ​​are determined. Based on the optimal air supply volume for multiple conditions, multiple flow deviation values, and multiple head deviation values, the initial air supply volume relationship is determined through regression analysis.

[0011] The present invention provides a method for controlling the active air supply volume of a hydro-turbine under low load. By determining multiple flow deviation values ​​and multiple head deviation values, it quantifies the deviation between the actual operating conditions and the optimal operating conditions of the hydro-turbine, providing core quantitative indicators for the nonlinear calculation of the air supply volume. Furthermore, by determining the initial air supply volume relationship through regression analysis, a nonlinear correlation model between the deviation values ​​and the air supply volume is established, enabling dynamic calculation of the air supply volume as the operating conditions deviate. This makes the air supply volume calculation more closely aligned with the actual operating patterns of the hydro-turbine. Therefore, by implementing this invention, a precise correlation between the air supply volume and the degree of deviation from the hydro-turbine operating conditions is achieved, thereby making the air supply volume calculation adaptable to the operating conditions and overcoming the problem of traditional air supply volume being disconnected from the operating conditions.

[0012] In one alternative implementation, the method further includes: The process involves acquiring a set of on-site low-load operating parameters for the turbine; modifying the initial air supply formula based on the on-site low-load operating parameters to obtain the target air supply formula; and using a programmable PLC controller to control the electromagnetic control valve to supply air to the turbine based on the target air supply formula.

[0013] The present invention provides a method for active air supply control of a hydro-turbine under low load. By acquiring a set of parameters for low-load operating conditions at the site, it can capture the actual operating characteristics of the hydro-turbine, providing a realistic data source for the field correction of the initial air supply formula. Furthermore, by correcting the initial formula using the field low-load operating condition parameter set to obtain the target formula, it compensates for the deviation between model tests and actual field conditions, thus making the air supply calculation formula more suitable for the field operating environment. Furthermore, by controlling air supply based on the target formula, the corrected and accurate formula can be applied to actual air supply control, improving the matching degree of air supply under low-load conditions. Therefore, by implementing this invention, the field adaptability correction of the initial air supply formula is achieved, thereby making the air supply calculation model highly consistent with the actual low-load operating conditions of the hydro-turbine, further improving the accuracy of field air supply control, and solving the problem of the disconnect between model tests and actual field conditions.

[0014] In one optional implementation, based on the on-site low-load operating condition parameter set, the initial gas replenishment quantity formula is modified to obtain the target gas replenishment quantity formula, including: Based on the on-site low-load operating condition parameter set, and through calculation of the initial air supply quantity relationship, multiple second air supply quantities of the turbine under on-site low-load operating conditions are determined. Based on the multiple second air supply quantities and the on-site low-load operating condition parameter set, the opening degree of the solenoid control valve is adjusted using a programmable PLC controller, and multiple third air supply quantities of the turbine under on-site low-load operating conditions are determined. Based on the initial air supply quantity relationship and the multiple third air supply quantities, the operating condition coefficient of the turbine is determined. Based on the operating condition coefficient and the initial air supply quantity relationship, the target air supply quantity relationship of the turbine is determined.

[0015] The present invention provides a method for controlling the active air supply volume of a hydro-turbine under low load. By calculating the second air supply volume on-site, an initial reference value is provided for the on-site air supply volume adjustment, clarifying the benchmark for on-site adjustment. Furthermore, by adjusting the solenoid valve to determine the third air supply volume, the optimal air supply volume adapted to the actual on-site operating conditions is obtained through actual on-site adjustment, ensuring the practicality of the air supply volume on-site. Furthermore, by determining the operating condition coefficient, the deviation coefficient between the actual on-site operating conditions and the model test is quantified, providing core parameters for the accurate correction of the initial relationship. Furthermore, by inputting the operating condition coefficient into the initial air supply volume relationship to obtain the target air supply volume relationship, the quantitative and accurate correction of the initial air supply volume relationship is achieved, thus ensuring that the target air supply volume relationship can fully adapt to the low-load operating conditions on-site. Therefore, by implementing this invention, through actual on-site adjustment and quantitative correction, a target air supply volume relationship that fully adapts to the low-load operating conditions of the hydro-turbine is obtained, making the air supply volume calculation more closely aligned with the actual on-site conditions and significantly improving the matching accuracy and control effect of the on-site air supply volume.

[0016] In one alternative implementation, the method further includes: The system acquires the initial unit efficiency and initial stability parameters of the turbine before air injection, as well as the target unit efficiency and target stability parameters after air injection. It then determines whether the target stability parameter is less than the initial stability parameter. If the target stability parameter is less than the initial stability parameter, it determines whether the target unit efficiency is less than the initial unit efficiency. If the target unit efficiency is greater than or equal to the initial unit efficiency, it controls the solenoid control valve to inject air into the turbine via a programmable PLC controller.

[0017] The present invention provides a method for controlling the active air supply to a turbine under low load. By acquiring efficiency and stability parameters before and after air supply, it provides direct data for the dual-indicator verification of the air supply effect, achieving a quantitative evaluation of the air supply effect. Furthermore, by judging whether the stability parameters have improved, the improvement effect of air supply on the stability of the turbine under low load operation is prioritized, effectively suppressing problems such as unit vibration and pressure pulsation. Furthermore, after stability improvement, by judging whether efficiency has decreased, a secondary verification of unit efficiency is performed under the premise of improving stability, avoiding unit efficiency loss due to air supply. Furthermore, air supply is controlled only after both indicators meet the standards, achieving air supply execution that ensures both stability and efficiency, thus enabling the air supply operation to simultaneously meet the requirements of stable and efficient unit operation. Therefore, by implementing this invention, a dual-indicator verification mechanism of efficiency and stability is established, realizing a closed-loop evaluation of the effect of air supply to the turbine under low load, ensuring that air supply effectively improves the stability of the unit under low load operation without reducing the unit's operating efficiency, while simultaneously considering the stability and economy of unit operation.

[0018] In one alternative implementation, the method further includes: When the target stability parameter value is greater than the initial stability parameter value, or the target unit efficiency value is less than the initial unit efficiency value, the first air supply is adjusted, and based on the adjusted first air supply, the electromagnetic control valve is controlled by the programmable PLC controller to supply air to the turbine.

[0019] The present invention provides a method for active air replenishment control of a turbine under low load. By adjusting the air replenishment volume and re-controlling it, the method can promptly correct the air replenishment volume and re-execute the air replenishment when the air replenishment effect fails to meet the dual requirements. This achieves dynamic optimization and adjustment of the air replenishment volume, ensuring that the final air replenishment effect meets both stability and efficiency requirements. Therefore, by implementing this invention, it is ensured that the air replenishment operation under low load conditions of the turbine can simultaneously meet the dual objectives of improving unit stability and maintaining efficiency, thus enhancing the fault tolerance and final effect of air replenishment control.

[0020] Secondly, the present invention provides a turbine low-load active air supply control system for executing the turbine low-load active air supply control method of the first aspect or any corresponding embodiment described above. The system is connected to the turbine. The system includes: an air supply calculation module, a programmable PLC controller, an electromagnetic control valve, and a flow meter. The air supply calculation module is used to determine the initial or target air supply relationship of the turbine under low load conditions and send the initial or target air supply relationship to the programmable PLC controller. The programmable PLC controller is used to adjust the opening of the solenoid control valve based on the initial or target air supply relationship. The solenoid control valve is used to control the air supply of the turbine. The flow meter is used to monitor the air supply of the turbine in real time.

[0021] The active air supply control system for low-load turbines provided by this invention accurately establishes and outputs an air supply calculation formula adapted to the low-load operating conditions of the turbine through an air supply calculation module, providing a core calculation basis for air supply control. Furthermore, a programmable PLC controller accurately receives the air supply formula and converts it into a solenoid valve opening adjustment signal, achieving intelligent and precise control of the air supply. Further, the opening of the solenoid control valve is precisely adjusted according to the PLC signal, ensuring precise execution of the air supply and guaranteeing a high degree of matching between the actual air supply and the calculated value. Furthermore, a flow meter is used to monitor the actual air supply in real time, providing real-time monitoring data for precise control and subsequent debugging and correction, ensuring the accuracy of air supply execution. Therefore, by implementing this invention, intelligent calculation, precise execution, and real-time monitoring of the air supply are achieved, ensuring the accuracy, efficiency, and controllability of the entire air supply control process, ultimately achieving stable and efficient operation of the turbine under low-load conditions.

[0022] Thirdly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to execute the turbine low-load active air supply control method described in the first aspect or any corresponding embodiment.

[0023] Fourthly, the present invention provides a computer program product, including computer instructions, which are used to cause a computer to execute the turbine low-load active air supply control method described in the first aspect or any corresponding embodiment. Attached Figure Description

[0024] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a structural block diagram of the turbine low-load active air supply control system according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of the active air supply control method for a water turbine under low load according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, 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.

[0027] It is understood that before using the technical solutions disclosed in the various embodiments of the present invention, users should be informed of the types, scope of use, and usage scenarios of the personal information involved in the present invention and their authorization should be obtained in accordance with relevant laws and regulations through appropriate means.

[0028] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0029] As an optional application scenario of this invention, such as Figure 1 As shown, a low-load active air supply control system 1 for a water turbine is provided. The low-load active air supply control system 1 is connected to the water turbine 2. It includes: an air supply calculation module 3, a programmable PLC controller 4, an electromagnetic control valve 5, and a flow meter 6.

[0030] Among them, the air replenishment calculation module 3 is used to determine the initial air replenishment formula or the target air replenishment formula of the turbine under low load conditions, and send the initial air replenishment formula or the target air replenishment formula to the programmable PLC controller.

[0031] Furthermore, the programmable PLC controller 4 is used to adjust the opening degree of the electromagnetic control valve 5 based on the initial air supply formula or the target air supply formula.

[0032] Furthermore, the electromagnetic control valve 5 is used to control the amount of air supplied to the turbine 2.

[0033] Furthermore, flow meter 6 is used to monitor the air supply of turbine 2 in real time.

[0034] Furthermore, by constructing a turbine low-load active air supply control system 1 that integrates air supply calculation, control, execution, and monitoring, it is possible to achieve intelligent calculation, precise execution, and real-time monitoring of air supply, ensuring the accuracy, efficiency, and controllability of the entire air supply control process, and ultimately achieving stable and efficient operation of the turbine under low-load conditions.

[0035] Furthermore, existing research on Qi replenishment has the following problems: 1. In the current method of air replenishment, the opening and closing of the air replenishment valve is usually controlled by a certain value. When the vacuum level weakens to a certain extent, the air replenishment valve often becomes inflexible and cannot open and close in time, causing the unit to vibrate violently and backflow. 2. The air replenishment valve does not take into account the air replenishment requirements under different actual operating conditions, resulting in poor air replenishment matching and a lack of verification mechanism, leading to poor air replenishment effect under low load conditions.

[0036] This invention provides a method for controlling the active air supply volume of a turbine under low load conditions. It realizes active air supply volume control based on real-time operating conditions under low load conditions, overcomes the defects of traditional fixed-value air supply, and makes the air supply volume adapt to the real-time operating conditions under low load, thereby improving the accuracy of air supply to the turbine under low load conditions and contributing to the stable operation of the unit under low load.

[0037] According to an embodiment of the present invention, a method for controlling the active air supply of a water turbine under low load is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0038] This embodiment provides a method for controlling the active air supply volume of a water turbine under low load, which can be used in the aforementioned active air supply volume control system 1 for water turbines under low load. Figure 2This is a flowchart of a method for controlling the active air supply to a water turbine under low load according to an embodiment of the present invention, as shown below. Figure 2 As shown, the process includes the following steps: Step S201: Obtain the multi-condition test dataset, real machine parameter set, model unit parameter set, and real-time operating condition parameter set of the turbine under the current low load condition.

[0039] In one optional embodiment, the multi-condition test dataset represents a collection of various operating data collected from the turbine under different operating conditions, which may include the flow rate of each operating condition. Water head Output power Stability parameters And other parameters. Furthermore, stability parameters. These can be field-measured values ​​representing changes in stability within the turbine runner, such as vibration values ​​of the unit's top cover or pressure pulsation values ​​of the tailrace pipe.

[0040] In one optional embodiment, the actual turbine parameter set represents the set of core technical parameters of the actual turbine of the power station during actual operation, which may include the rated head of the power station. Maximum water head Minimum water head Optimal operating flow rate Actual machine rotor diameter Actual machine speed wait.

[0041] In an optional embodiment, the model unit parameter set represents the set of core technical parameters of the model unit used for conducting turbine air supply model tests, and may include the model unit runner diameter. Model unit speed Optimal operating flow rate wait.

[0042] In one optional embodiment, the current low-load condition refers to the turbine operating at 0-45% load, which is the range where the existing air supply method is ineffective. Furthermore, under this condition, the turbine is prone to stability problems such as cavitation, vibration, and sway due to turbulence at the runner inlet and outlet.

[0043] In one optional embodiment, the real-time operating parameter set represents the set of operating parameters collected in real time by the unit monitoring and condition monitoring system under the current low-load operating condition of the turbine, which may include real-time flow rate. Water head Output power Stability parameters Parameters such as these.

[0044] Step S202: Based on the actual machine parameter set and the model unit parameter set, determine the optimal air supply for the turbine model unit under multiple operating conditions under multiple low-load test conditions.

[0045] In one optional embodiment, based on the core technical parameters of the actual turbine and the model unit, through professional parameter conversion and targeted tests of the model unit, the optimal air supply volume of the model unit can be determined to simultaneously meet the requirements of reduced pressure pulsation and no reduction in unit efficiency under multiple test conditions simulating low-load operation of the actual turbine, i.e., the optimal air supply volume for multiple operating conditions.

[0046] For example, when the model unit and the real machine meet the requirements of geometric similarity, kinematic similarity, and dynamic similarity, the operating performance of the model unit can be accurately converted to that of the real machine. Therefore, the air replenishment volume rules obtained through its experiments can be transferred and applied to the real machine. Furthermore, based on this, the low-load operating parameters of the real machine can be converted to the model unit, and multiple low-load operating scenarios of the real machine can be reproduced on the model unit to conduct air replenishment volume tests. At the same time, based on the dual-core judgment criteria of improved stability without reduced efficiency, the optimal air replenishment volume under each test condition can be selected, ensuring that the air replenishment volume is adapted to the air replenishment requirements of the real machine under the corresponding low-load operating conditions.

[0047] Step S203: Based on the multi-condition test dataset, the actual machine parameter set, and the optimal air replenishment volume for multiple conditions, the initial air replenishment volume relationship is determined through regression analysis.

[0048] In an alternative embodiment, the regression analysis method refers to a mathematical statistics method for studying the dependence between a dependent variable and one or more independent variables.

[0049] In one optional embodiment, the air supply requirement of the turbine under low-load conditions is determined by the degree of deviation between its actual operating conditions and the optimal operating conditions. Different deviations in flow rate and head from the optimal values ​​result in non-linear variations in the required optimal air supply. Therefore, based on this logic, this embodiment utilizes a multi-condition test dataset, a real machine parameter set, and multiple optimal air supply amounts for different operating conditions. Through regression analysis, a quantitative mathematical formula can be fitted between the turbine's air supply and operating condition deviations (flow rate deviation, head deviation), i.e., the initial air supply relationship.

[0050] Step S204: Based on the real-time operating condition parameter set, the first air supply of the turbine under the current low load condition is obtained by calculating the initial air supply relationship.

[0051] In one optional embodiment, the air supply demand of the turbine under low load is determined by the deviation between its actual real-time operating conditions and the optimal operating conditions. The initial air supply formula has been constructed using mathematical methods to establish a quantitative functional relationship between the flow deviation ratio, the head deviation ratio, and the air supply. Therefore, based on this initial air supply formula, the flow rate and head parameters of the real-time operating conditions are converted into corresponding deviation ratios. The first air supply quantity that highly matches the current low-load real-time operating conditions can then be calculated using this initial air supply formula. This achieves dynamic and quantitative calculation of the air supply quantity according to the operating conditions, breaking through the limitations of traditional fixed-value air supply.

[0052] Step S205: Based on the first air replenishment volume, the electromagnetic control valve is controlled by the programmable PLC controller to replenish air to the turbine.

[0053] In an optional embodiment, the programmable PLC controller 4 utilizes its computing and control capabilities to output a corresponding control signal to adjust the opening of the electromagnetic control valve based on the obtained first air replenishment amount. This enables the turbine low-load active air replenishment control system 1 to input a precise first air replenishment amount to the turbine 2, thereby completing the process from calculating the air replenishment amount to implementing the actual air replenishment operation.

[0054] For example, after receiving the first air replenishment quantity, the programmable PLC controller 4 retrieves the pre-stored mapping relationship between the air replenishment quantity and the opening degree of the electromagnetic control valve. Then, the programmable PLC controller 4 can convert the first air replenishment quantity value into the corresponding electromagnetic control valve opening degree control signal, i.e., an electrical signal, according to the mapping relationship.

[0055] Furthermore, the programmable PLC controller 4 outputs the opening control signal to the solenoid control valve 5, and triggers the solenoid control valve 5 to adjust its own opening to the corresponding position according to the signal.

[0056] Furthermore, the turbine low-load active air replenishment control system 1 can deliver an air volume matching the first air replenishment volume to the turbine 2 by adjusting the opening of the electromagnetic control valve 5, and complete the air replenishment operation under the current low-load condition.

[0057] Furthermore, during the air replenishment process, the flow meter 6 in the turbine low-load active air replenishment control system 1 can also monitor the actual air replenishment volume in real time and feed the monitoring data back to the programmable PLC controller 4, thereby enabling real-time monitoring of the air replenishment volume.

[0058] The active air replenishment control method for turbines under low load provided in this embodiment realizes active air replenishment control based on real-time operating conditions under low load conditions, overcoming the shortcomings of traditional fixed-value air replenishment, thereby making the air replenishment volume adapt to the real-time operating conditions under low load, improving the accuracy of turbine air replenishment under low load, and helping the unit to operate stably under low load.

[0059] In some optional implementations, step S202 above includes: Step S2021: Based on the actual machine parameter set and the model unit parameter set, the head values ​​and optimal flow values ​​of multiple model units are obtained through similarity conversion methods.

[0060] In an optional embodiment, when the model unit and the real machine satisfy geometric similarity, kinematic similarity and dynamic similarity, there is a fixed similarity conversion relationship between their hydraulic performance parameters. Therefore, through this relationship, the operating parameters of the real machine, such as head and flow rate, can be accurately converted into the test parameters of the model unit, namely, multiple model unit head values ​​and the optimal flow rate value of the model unit. This ensures that the test conditions of the model unit can truly reproduce the actual operating conditions of the real machine, that is, the test results can be effectively transferred to the real machine.

[0061] For example, the rated head, maximum head, and minimum head of the model unit can be calculated based on the similarity conversion relationship of the water turbine, as shown in the following formulas (1) to (3): (1) (2) (3) In the formula: Indicates the rated head value; Indicates the maximum head value; This represents the minimum head value.

[0062] Furthermore, the optimal flow rate of the model unit can be calculated based on the similarity conversion relationship of the water turbine, as shown in the following equation (4): (4) In the formula: This represents the optimal flow rate value for the model unit.

[0063] Step S2022: Based on the optimal flow rate value of the model unit, determine multiple low-load test conditions for the turbine model unit.

[0064] In one optional embodiment, the optimal flow rate of the model unit is used as a benchmark to determine the flow range and specific operating point of the low-load gas supply test of the model unit, thereby ensuring that the test conditions can fully cover the actual low-load operating range of the real machine.

[0065] For example, the optimal flow rate of the model unit can be used. The flow range for the low-load gas supply test of the model unit was determined as follows: Furthermore, this range matches the flow rate range of the actual machine under low load conditions of 0-45%.

[0066] Furthermore, with For fixed intervals, in Ten flow test points are selected within the range, and each flow test point corresponds to a low-load test condition of the model unit.

[0067] Furthermore, the above 10 flow test points were integrated and identified as multiple low-load test conditions for the model unit to conduct gas replenishment tests.

[0068] Step S2023: Based on the head values ​​of multiple model units, the air supply volume of the turbine model units is tested under multiple low-load test conditions, and the optimal air supply volume value for multiple conditions is determined.

[0069] In one optional embodiment, the vortex and cavitation states within the turbine runner differ under low-load conditions with different heads and flow rates, resulting in variations in the required air supply. The core objective of air supply is to effectively reduce pressure pulsation / vibration (improving stability) without causing unit efficiency loss. Therefore, in this embodiment, using multiple model unit head values ​​and multiple low-load test conditions, air supply tests are conducted on the model units under a full range of operating conditions. Based on the dual-core criterion of improved stability without reduced efficiency, the optimal air supply for each test condition is selected, i.e., the optimal air supply values ​​for multiple operating conditions.

[0070] For example, a test platform for the make-up air volume of the model unit is built, and the model unit is equipped with a make-up air system, an efficiency monitoring device, and a stability parameter (top cover vibration / tailwater pipe pressure pulsation) monitoring device.

[0071] Furthermore, the gas supply can be tested sequentially for each of the 10 low-load test conditions under each model unit's head value, according to the combination of head and flow rate: ① Fix a certain model head and a certain low load flow condition, and monitor the efficiency and stability parameters of the model unit before gas injection as benchmark data.

[0072] ② Gradually adjust the amount of supplemental air in the supplemental air system, and stabilize the flow field after each adjustment. Monitor and record the unit efficiency and stability parameters under the corresponding supplemental air amount.

[0073] Furthermore, for all the air replenishment test data of each head-flow combination test condition, based on the judgment criteria that the pressure pulsation / vibration amplitude decreases (stability improves) and the unit efficiency is not lower than the baseline value before air replenishment, the air replenishment volume that meets the criteria is selected.

[0074] Furthermore, from the replenishment air volume that meets the standard, the replenishment air volume that can achieve the best stability improvement effect is determined as the optimal replenishment air volume value under the test condition. Then, after completing the testing and screening of the head values ​​of all model units and all low-load test conditions, multiple optimal replenishment air volume values ​​corresponding to each test condition can be obtained.

[0075] In some optional implementations, step S203 above includes: Step S2031: Based on the multi-condition test dataset and the actual machine parameter set, determine multiple flow deviation values ​​and multiple head deviation values.

[0076] In one optional embodiment, the air supply requirement of the turbine under low load is determined by the degree of deviation between its actual operating conditions and the optimal operating conditions. The greater the deviation of the flow rate and head from the optimal / rated operating conditions, the higher the adaptability requirement of the required air supply. Therefore, by converting the difference between the actual operating parameters and the reference parameters into a proportional deviation value, the influence of parameter dimensions can be eliminated, and the uniform quantification of the deviation degree of different operating conditions can be achieved, so that the deviation value can directly participate in the construction of the functional relationship of the air supply.

[0077] In one optional embodiment, the actual operating parameters of each operating condition in the operating condition test dataset are used, and the optimal and rated benchmark parameters in the real machine parameter set are combined, and the flow deviation ratio and head deviation ratio corresponding to each test operating condition are obtained through standardized calculation, thereby converting the degree of operating condition deviation into a quantitative indicator that can participate in mathematical modeling.

[0078] For example, for each test condition, the flow deviation and head deviation can be calculated using the following relationships (5) and (6): (5) (6) In the formula: Indicates the flow deviation value; This indicates the head deviation value.

[0079] Step S2032: Based on the optimal air supply volume under multiple operating conditions, multiple flow deviation values, and multiple head deviation values, the initial air supply volume relationship is determined through regression analysis.

[0080] In one alternative embodiment, the air supply to the turbine is non-linearly related to the ratio of flow rate and head deviation, and cannot be described by a simple linear formula. Regression analysis, however, can use mathematical statistics to fit multiple sets of sample data, uncover the inherent non-linear relationship between independent and dependent variables, and determine the specific functional expression by solving for the unknown parameters.

[0081] Therefore, in this embodiment, the obtained flow deviation value and head deviation value The independent variable and the optimal replenishment volume under each working condition are used as the optimal replenishment volume value (dependent variable) for each working condition as sample data. By performing data fitting through regression analysis, a mathematical formula that can accurately describe the nonlinear relationship among the three can be obtained, namely the initial replenishment volume relationship, as shown in the following relationship (7): (7) In the formula: This indicates the amount of Qi to be replenished.

[0082] In some optional implementations, the above method further includes: Step a1: Obtain the set of on-site low-load operating parameters for the turbine.

[0083] In one optional embodiment, the model test is conducted under ideal test conditions, while the actual turbine in the field is affected by factors such as flow channel wear, water quality, and load fluctuations, making the initial formula unable to fully adapt to the field conditions. Therefore, by collecting the actual operating parameters of the turbine in the field under low load conditions of 0-45%, i.e., the field low load condition parameter set, subsequent corrections can be made closer to the actual turbine operating state, improving the accuracy of air supply control.

[0084] For example, multiple typical operating conditions with different head and flow combinations are selected within the 0-45% low load range on site, and parameters for each operating condition are collected through the unit monitoring system, which may include real-time flow, real-time head, output power, stability parameters, etc.

[0085] Furthermore, abnormal data is removed, and corresponding on-site low-load operating condition parameter sets are compiled.

[0086] Step a2: Based on the on-site low-load operating condition parameter set, the initial gas replenishment quantity relationship is modified to obtain the target gas replenishment quantity relationship.

[0087] In one optional embodiment, the actual optimal air replenishment volume that satisfies the requirements of improved stability without reduced efficiency is obtained through on-site debugging. The deviation between the theoretical value of the model and the actual value on-site is quantified by the operating condition coefficient. Then, the coefficient is incorporated into the initial air replenishment volume relationship to obtain the target air replenishment volume relationship, thus realizing the on-site adaptation of the air replenishment volume relationship.

[0088] Specifically, step a2 above includes: Step a21: Based on the on-site low-load operating condition parameter set, and through the calculation of the initial air supply relationship, determine multiple second air supply quantities for the turbine under on-site low-load operating conditions.

[0089] Step a22: Based on multiple second air supply volumes and a set of on-site low-load operating parameters, the opening degree of the solenoid control valve is adjusted using a programmable PLC controller, and multiple third air supply volumes of the turbine under on-site low-load operating conditions are determined.

[0090] Step a23: Based on the initial air supply formula and multiple third air supply quantities, determine the operating coefficient of the turbine.

[0091] Step a24: Based on the operating condition coefficient and the initial air supply relationship, determine the target air supply relationship for the turbine.

[0092] Step a3: Based on the target air supply formula, the electromagnetic control valve is controlled by a programmable PLC controller to supply air to the turbine.

[0093] In an alternative embodiment, parameters can be centrally extracted based on on-site low-load operating conditions. , Extract real device parameters , Then, the flow deviation value is calculated using the above relationships (5) and (6). and head deviation value .

[0094] Furthermore, by substituting the above parameters into the initial air replenishment relationship shown in the above relationship (7), the theoretical air replenishment for each working condition, i.e., the second air replenishment, can be calculated.

[0095] Furthermore, for each set of on-site working conditions, the initial efficiency and initial stability parameters when no air is replenished are monitored, and the electromagnetic control valve 5 is controlled by the programmable PLC controller 4 based on the second air replenishment volume, and the air replenishment volume is increased / decreased in steps of 5%-10%.

[0096] Furthermore, after each adjustment, the flow field is stabilized, and real-time stability parameters and real-time efficiency values ​​are monitored. If the real-time stability parameter is less than the initial stability parameter and lower than the standard value, the efficiency is further evaluated. If the real-time efficiency value does not decrease, the adjustment is reversed until the real-time efficiency value decreases and meets the standard.

[0097] Furthermore, if the adjusted real-time efficiency value is greater than or equal to the initial efficiency, then the replenishment gas volume is set as the third replenishment gas volume.

[0098] Furthermore, for each set of working conditions, the single-working-condition coefficient is calculated using the following formula (8). : (8) In the formula: This indicates the third amount of supplementary Qi.

[0099] Furthermore, if each If the distribution is uniform, the average value is taken as the final operating condition coefficient. Furthermore, if each If there is a nonlinear relationship with the operating condition deviation, the final operating condition coefficient can be obtained through nonlinear fitting. .

[0100] Furthermore, it can be verified The universality of this is to ensure that the deviation between the corrected calculated gas replenishment volume and the actual value on site is within the allowable range of the project.

[0101] Furthermore, the obtained working condition coefficients By incorporating the initial air replenishment volume relationship, the corresponding target air replenishment volume relationship is obtained, as shown in the following relationship (9): (9) Furthermore, based on the obtained target air supply formula, the electromagnetic control valve 5 is controlled by the programmable PLC controller 4 to supply air to the turbine 2.

[0102] The specific control process can be referred to in steps S204 to S205 above, where the electromagnetic control valve 5 is controlled by the programmable PLC controller 4 to replenish the turbine 2 with air based on the initial air replenishment formula. It will not be repeated here.

[0103] In some optional implementations, the above method further includes: Step b1: Obtain the initial unit efficiency value and initial stability parameter value of the turbine before air injection, and the target unit efficiency value and target stability parameter value of the turbine after air injection.

[0104] Step b2: Determine whether the target stability parameter value is less than the initial stability parameter value.

[0105] Step b3: When the target stability parameter value is less than the initial stability parameter value, determine whether the target unit efficiency value is less than the initial unit efficiency value.

[0106] Step b4: When the target unit efficiency value is greater than or equal to the initial unit efficiency value, the electromagnetic control valve is controlled by the programmable PLC controller to replenish air to the turbine.

[0107] Step b5: When the target stability parameter value is greater than the initial stability parameter value, or the target unit efficiency value is less than the initial unit efficiency value, adjust the first air supply volume, and based on the adjusted first air supply volume, control the electromagnetic control valve to supply air to the turbine through the programmable PLC controller.

[0108] In an optional embodiment, initial stability parameters are monitored and recorded before starting the gas injection system. Meanwhile, the data acquisition unit output power ,flow Water head The initial unit efficiency value is calculated according to the following formula (10). : (10) Furthermore, the gas injection system is activated and gas is continuously injected for 2-5 minutes to stabilize the flow field, and then the stability parameters after gas injection are monitored and recorded. Meanwhile, the data acquisition unit output power ,flow Water head And calculate the unit efficiency value after gas replenishment.

[0109] Furthermore, the stability parameters after gas replenishment... Stability parameters before Qi replenishment Compare them, and then, if If the stability parameters are determined to have improved, then the unit efficiency value after gas replenishment will continue to be adjusted. Unit efficiency value before gas replenishment Compare them.

[0110] Furthermore, if If the efficiency is not reduced, then the programmable PLC controller 4 can continue to control the electromagnetic control valve 5 to replenish the water turbine 2 with air.

[0111] Furthermore, if If the efficiency is reduced, the first air supply is adjusted, and based on the adjusted first air supply, the electromagnetic control valve 5 continues to supply air to the turbine 2 through the programmable PLC controller 4.

[0112] Furthermore, if If the stability parameters are not improved, the first air supply volume is adjusted, and based on the adjusted first air supply volume, the electromagnetic control valve 5 is controlled by the programmable PLC controller 4 to supply air to the turbine 2.

[0113] In one example, a low-load active air replenishment control system for a hydro turbine is provided. The system includes three modules: an operation data acquisition module, an air replenishment calculation and execution module, and an air replenishment verification and feedback module. These modules respectively acquire operating parameters, calculate and execute air replenishment, adjust air replenishment, and verify the effect feedback. The system dynamically determines the air replenishment based on the deviation between the real-time operating conditions and the optimal operating conditions of the hydro turbine, and avoids excessive air replenishment through dual verification of stability and efficiency.

[0114] Furthermore, in practical implementation, on-site commissioning and adjustment steps can be added to optimize the accuracy of the air supply determination, ensuring that the air supply can effectively suppress pressure pulsations and vibrations caused by eddies, thereby improving the operational stability of units operating under wide loads. Specifically, this includes: 1. Data Acquisition Module: Communicates with the unit monitoring and condition monitoring system to obtain the flow rate under current operating conditions. Water head Output power Stability parameters Parameters such as computer group efficiency Stability parameters These can be field-measured values ​​representing changes in stability within the turbine runner, such as vibration values ​​of the unit's top cover or pressure pulsation values ​​of the tailrace pipe.

[0115] 2. Gas replenishment calculation module. This can be determined using experimental or simulation methods; here, we take a model experiment as an example.

[0116] 2.1 First, obtain the rated head of the power station. , , and optimal operating flow rate The diameter of the actual power plant unit and speed .

[0117] 2.2 Calculate the required head for the model unit to be tested on the model test bench based on the similarity conversion method. , , , The specific method is as follows: First, obtain the diameter of the model unit. and speed Then calculate according to the above relationships (1) to (4).

[0118] 2.3 Air supply tests were conducted at the maximum, minimum, and rated heads of the model unit. For each of the three heads, the following parameters were selected: Range, every The air supply volume for each of the 10 intermittent operating conditions was determined by using the criterion that the pressure pulsation before and after air replenishment should decrease without a decrease in efficiency.

[0119] 2.4 Based on the obtained air supply volume, considering the nonlinear relationship between air supply volume and flow rate head under each operating condition, regression analysis is used to establish the relationship between operating conditions and air supply volume.

[0120] 2.4.1 Calculate the flow rate and head under each working condition and the flow rate deviation ratio from the optimal working condition, as shown in the above relationships (5) and (6).

[0121] 2.4.2 Determine the formula for the amount of gas to be added in the regression analysis based on the deviation ratio, as shown in the above relationship (7).

[0122] 3. Design of the air replenishment execution system.

[0123] 3.1 Add a programmable PLC controller, solenoid control valve, and flow meter to the existing air replenishment system.

[0124] 3.2 Input the air replenishment calculation formula determined in step 2 into the PLC programmable controller so that it can automatically calculate the air replenishment amount according to the flow rate and head under each working condition.

[0125] 3.3 The PLC controller outputs the opening signal of the solenoid valve according to the air replenishment amount, and adjusts the opening of the solenoid valve to achieve the required air replenishment amount.

[0126] 4. The formulas in the PLC programmable controller can be further modified through on-site debugging.

[0127] 4.1 Determine the required air supply volume for a specific operating condition at the power plant site. First, calculate the initial air supply volume for the test condition using the existing formulas in the PLC.

[0128] 4.2 Adjust the solenoid valve opening to increase or decrease the air supply by 5%-10% and judge the stability parameters. If the increase in air supply is smaller than the standard value, proceed to the next step. If the increase is smaller and falls below the standard value, adjust the air supply in the opposite direction until the increase is achieved. If the value decreases and falls below the standard value, proceed to the next step.

[0129] 4.3 Determine whether the efficiency has decreased after adjusting the air supply volume. If not, set the air supply volume for the current operating condition to the final value. .

[0130] 4.4 Determine the amount of supplementary gas based on step 2. The formula and the air supply volume determined during on-site commissioning Determine the current operating condition coefficient Multiple sets of tests can be conducted, and the coefficients in the air replenishment formula can be determined based on the average value of the air replenishment coefficient under multiple operating conditions or the nonlinear relationship. .

[0131] 4.5 Write the coefficient into the PLC controller, and the final formula is as shown in the above relation (9).

[0132] 5. Dual feedback verification module for air supply. Based on the stability parameters of the turbine. With a dual feedback mechanism for efficiency, precise dynamic adjustment of the amount of supplementary air is achieved.

[0133] 5.1 Efficiency of the computer unit before starting the gas supply system at the power plant With stability parameters .

[0134] 5.2 Start the air replenishment system. The PLC determines the air replenishment volume and solenoid valve opening based on the current operating parameters and performs air replenishment.

[0135] 5.3 After the gas injection continues for a period of time (approximately 2-5 minutes to stabilize the flow field), monitor the unit efficiency again. and The effectiveness of turbine air supply is evaluated in real time using efficiency and stability as dual verification indicators.

[0136] 5.4 First, determine whether stability parameters such as the vibration amplitude of the top cover have improved. If the condition is met, then the efficiency is checked.

[0137] 5.5 If efficiency Then continue to replenish Qi. If Then return to step 3 to adjust the air replenishment amount. Each time, replenish the air by decreasing or increasing the air replenishment amount by 5%-10% until the requirements are met.

[0138] The active air supply control system for low-load turbines provided in this example has the following effects: 1. Based on the deviation of flow rate and head under various operating conditions from the optimal flow rate and rated head, a nonlinear formula for calculating the air replenishment volume is proposed. Based on a programmable air replenishment valve, the targeted air replenishment volume for each operating condition is realized, which is different from the problem that existing air replenishment valves cannot adjust the air replenishment volume according to the operating conditions.

[0139] 2. Efficiency and stability parameters are used as the verification and adjustment of the gas supply volume to ensure that the unit efficiency is not reduced while the stability is improved by gas supply, thus solving the problem of the impact of the evolution of the site environment on the gas supply effect.

[0140] 3. By dynamically adjusting the gas supply based on changes in actual operating conditions and providing feedback verification, the vibration of the turbine was effectively reduced, ensuring that the unit efficiency was not affected. This enabled the turbine to operate safely and stably within a wider range, better serving the consumption of new energy sources in the new power system.

[0141] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention.

[0142] The following is a detailed reference. Figure 3 The diagram illustrates a structural schematic suitable for implementing an electronic device according to embodiments of the present invention. The electronic device may include a processor (e.g., a central processing unit, graphics processor, etc.) 301, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 302 or a program loaded from memory 308 into random access memory (RAM) 303. The RAM 303 also stores various programs and data required for the operation of the electronic device. The processor 301, ROM 302, and RAM 303 are interconnected via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0143] Typically, the following devices can be connected to I / O interface 305: input devices 306 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 307 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; memory devices 308 including, for example, magnetic tapes, hard disks, etc.; and communication devices 309. Communication device 309 allows electronic devices to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 3 Electronic devices with various devices are shown, but it should be understood that it is not required to implement or have all of the devices shown, and more or fewer devices may be implemented or have instead.

[0144] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 309, or installed from a memory 308, or installed from a ROM 302. When the computer program is executed by the processor 301, it performs the functions defined in the turbine low-load active air supply control method of the embodiments of the present invention.

[0145] Figure 3 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present invention.

[0146] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the turbine low-load active air supply control method shown in the above embodiments is implemented.

[0147] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0148] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for controlling the active air supply volume of a water turbine under low load, characterized in that, A low-load active air supply control system for a hydro turbine, the system being connected to the hydro turbine, the system including a programmable PLC controller and electromagnetic control valves; the method includes: Acquire the multi-condition test dataset of the turbine, the actual machine parameter set, the model unit parameter set, and the real-time operating condition parameter set of the turbine under the current low-load condition; Based on the actual machine parameter set and the model unit parameter set, the optimal air supply for the model unit of the water turbine under multiple low-load test conditions is determined. Based on the multi-condition test dataset, the actual machine parameter set, and the optimal air replenishment volume for the multiple conditions, the initial air replenishment volume relationship is determined through regression analysis. Based on the real-time operating condition parameter set, the first air supply of the turbine under the current low load condition is obtained by calculating the initial air supply relationship. Based on the first air replenishment volume, the programmable PLC controller controls the electromagnetic control valve to replenish air to the water turbine.

2. The method according to claim 1, characterized in that, Based on the actual turbine parameter set and the model unit parameter set, the optimal air injection rate for the turbine under multiple low-load test conditions is determined, including: Based on the actual machine parameter set and the model unit parameter set, multiple model unit head values ​​and optimal flow rates are obtained through similarity conversion methods. Based on the optimal flow rate value of the model unit, the multiple low-load test conditions of the turbine model unit are determined; Based on the head values ​​of the multiple model units, the air supply volume of the turbine model units was tested under the multiple low-load test conditions, and the optimal air supply volume value for the multiple conditions was determined.

3. The method according to claim 1, characterized in that, Based on the multi-condition test dataset, the actual machine parameter set, and the optimal air injection volume for the multiple conditions, the initial air injection volume relationship is determined through regression analysis, including: Based on the multi-condition test dataset and the actual machine parameter set, multiple flow deviation values ​​and multiple head deviation values ​​are determined; Based on the optimal air supply for the multiple operating conditions, the multiple flow rate deviations, and the multiple head deviations, the initial air supply relationship is determined through the regression analysis method.

4. The method according to claim 1, characterized in that, The method further includes: Obtain the set of on-site low-load operating parameters for the turbine. Based on the set of on-site low-load operating conditions parameters, the initial gas replenishment formula is modified to obtain the target gas replenishment formula. Based on the target air supply formula, the electromagnetic control valve is controlled by a programmable PLC controller to supply air to the turbine.

5. The method according to claim 4, characterized in that, Based on the aforementioned low-load operating condition parameter set, the initial gas supply formula is modified to obtain the target gas supply formula, including: Based on the set of on-site low-load operating parameters, and through the calculation of the initial air supply relationship, multiple second air supply quantities of the turbine under on-site low-load operating conditions are determined. Based on the multiple second air supply volumes and the on-site low-load operating condition parameter set, the opening degree of the electromagnetic control valve is adjusted using the programmable PLC controller, and multiple third air supply volumes of the turbine under the on-site low-load operating condition are determined. Based on the initial air supply formula and the multiple third air supply quantities, the operating condition coefficient of the turbine is determined; Based on the operating condition coefficient and the initial air supply relationship, the target air supply relationship of the turbine is determined.

6. The method according to claim 1, characterized in that, The method further includes: Obtain the initial unit efficiency value and initial stability parameter value of the turbine before air injection, and the target unit efficiency value and target stability parameter value of the turbine after air injection; Determine whether the target stability parameter value is less than the initial stability parameter value; If the target stability parameter value is less than the initial stability parameter value, determine whether the target unit efficiency value is less than the initial unit efficiency value; When the target unit efficiency value is greater than or equal to the initial unit efficiency value, the electromagnetic control valve is controlled by the programmable PLC controller to supply air to the turbine.

7. The method according to claim 6, characterized in that, The method further includes: When the target stability parameter value is greater than the initial stability parameter value, or the target unit efficiency value is less than the initial unit efficiency value, the first air supply is adjusted, and based on the adjusted first air supply, the electromagnetic control valve is controlled by the programmable PLC controller to supply air to the turbine.

8. A low-load active air supply control system for a water turbine, characterized in that, The system is used to implement the active air supply control method for low-load turbines according to any one of claims 1 to 7, wherein the system is connected to the turbine; the system includes: an air supply calculation module, a programmable PLC controller, an electromagnetic control valve, and a flow meter; The air supply calculation module is used to determine the initial air supply relationship or the target air supply relationship of the turbine under low load conditions, and send the initial air supply relationship or the target air supply relationship to the programmable PLC controller. The programmable PLC controller is used to adjust the opening degree of the electromagnetic control valve based on the initial air supply formula or the target air supply formula. The electromagnetic control valve is used to control the amount of air supplied to the water turbine; The flow meter is used to monitor the air supply of the turbine in real time.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the turbine low-load active air supply control method according to any one of claims 1 to 7.

10. A computer program product, characterized in that, Includes computer instructions, which are used to cause a computer to execute the turbine low-load active air replenishment control method according to any one of claims 1 to 7.

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