Intelligent static blade angle adjusting method and system under low-load working condition of steam turbine

Abstract

The invention discloses an intelligent static blade angle adjusting method and system for a steam turbine under the low-load working condition, and the method comprises the steps that real-time operation data of the steam turbine under the low-load working condition are obtained, and the real-time operation data comprise a flow parameter, a pressure parameter and a temperature parameter; and according to the real-time operation data, the aerodynamic characteristic change trend under the current working condition is calculated, and the optimal value of the theoretical stationary blade angle is determined. And comparing the deviation between the theoretical optimal value and the actual static blade angle value, and judging whether adjustment is needed or not. And if the deviation exceeds a preset threshold value, a stationary blade angle adjusting mechanism is started, and an adjusting instruction is generated. And the adjusting instruction is input into an executing mechanism, and the target angle of the static blade angle value is adjusted. Therefore, the method can intelligently adapt to aerodynamic characteristic changes under the low-load working condition, accurate adjustment of the static blade angle is achieved, and the operation efficiency and stability of the steam turbine under the low-load condition are effectively improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of energy and power station technology, and in particular to a method and system for intelligently adjusting the stator blade angle of a steam turbine under low-load conditions. Background Art

[0002] With the continuous growth of energy demand and the rapid development of the power industry, steam turbines, as important power equipment, are increasingly widely used in power stations and other fields. However, in the actual operation of steam turbines, especially under low-load conditions, their aerodynamic characteristics will change significantly, resulting in reduced operating efficiency and stability. Under low-load conditions, parameters such as flow, pressure and temperature of the steam turbine will change, and these changes directly affect the aerodynamic characteristics of the steam turbine, such as flow field distribution, efficiency, stability, etc. If the stator blade angle cannot be adjusted in a timely and accurate manner to adapt to these changes, the performance of the steam turbine will be reduced, and even cause failures. Summary of the invention

[0003] The embodiment of the present invention provides a method and system for intelligently adjusting the stator blade angle under low-load conditions of a steam turbine, which can intelligently adapt to changes in aerodynamic characteristics under low-load conditions, achieve precise adjustment of the stator blade angle, and effectively improve the operating efficiency and stability of the steam turbine under low-load conditions.

[0004] To achieve the above-mentioned purpose, in the first aspect, the present invention provides a method for intelligently adjusting the stator blade angle under low-load conditions of a steam turbine, comprising: obtaining real-time operating data of the steam turbine under low-load conditions, wherein the real-time operating data includes flow parameters, pressure parameters and temperature parameters. According to the real-time operating data, the aerodynamic characteristics change trend under the current operating conditions is calculated to determine the theoretical optimal value of the stator blade angle. The deviation between the theoretical optimal value and the actual stator blade angle value is compared to determine whether adjustment is required. If the deviation exceeds a preset threshold, the stator blade angle adjustment mechanism is started and an adjustment instruction is generated. The adjustment instruction is input into the actuator to adjust the stator blade angle value to a target angle.

[0005] In one embodiment of the present invention, the real-time operating data of the steam turbine under low load conditions is obtained, wherein the real-time operating data includes flow parameters, pressure parameters and temperature parameters, including: obtaining the steam turbine operating data in real time through a sensor, wherein the operating data includes flow parameters, pressure parameters and temperature parameters; cleaning the obtained operating data to remove abnormal values ​​and noise to obtain the cleaned real-time operating data.

[0006] In one embodiment of the present invention, the calculation of the aerodynamic characteristics change trend under the current operating conditions based on the real-time operating data and the determination of the theoretical optimal value of the stator blade angle include: establishing a correlation model among flow values, pressure values ​​and temperature values ​​using a regression method based on the real-time operating data; calculating the aerodynamic change under the current operating conditions through the correlation model to obtain the aerodynamic characteristics change trend; determining the theoretical optimal value of the stator blade angle based on the aerodynamic characteristics change trend in combination with a preset aerodynamic performance optimization algorithm.

[0007] In one embodiment of the present invention, the comparison of the deviation between the theoretical optimal value and the actual stator blade angle value to determine whether adjustment is needed includes: obtaining the real-time stator blade angle value of the steam turbine under the current operating conditions through a sensor; comparing the theoretical optimal stator blade angle value with the actual stator blade angle value to calculate the deviation between the two; and determining whether adjustment is needed based on the deviation value.

[0008] In the second aspect, the present invention provides an intelligent stator blade angle adjustment system under low-load conditions of a steam turbine, comprising: an acquisition module, a determination module, a judgment module, a generation module and an adjustment module. The acquisition module is used to obtain real-time operating data of the steam turbine under low-load conditions, wherein the real-time operating data includes flow parameters, pressure parameters and temperature parameters. The determination module is used to calculate the aerodynamic characteristics change trend under the current operating conditions based on the real-time operating data, and determine the theoretical stator blade angle optimal value. The judgment module is used to compare the deviation between the theoretical optimal value and the actual stator blade angle value to determine whether adjustment is required. The generation module is used to start the stator blade angle adjustment mechanism and generate an adjustment instruction if the deviation exceeds a preset threshold. The adjustment module is used to input the adjustment instruction into the actuator to adjust the stator blade angle value to a target angle.

[0009] In one embodiment of the present invention, the acquisition module includes: a first acquisition unit and a first obtaining unit. The first acquisition unit is used to obtain steam turbine operation data in real time through a sensor, and the operation data includes flow parameters, pressure parameters and temperature parameters. The first obtaining unit is used to clean the acquired operation data, remove abnormal values ​​and noise, and obtain the cleaned real-time operation data.

[0010] In one embodiment of the present invention, the determination module includes: an establishment unit, a second obtaining unit and a determination unit. The establishment unit is used to establish a correlation model between flow values, pressure values ​​and temperature values ​​using a regression method based on the real-time operation data. The second obtaining unit is used to calculate the aerodynamic change under the current working conditions through the correlation model to obtain the aerodynamic characteristic change trend. The determination unit is used to determine the optimal value of the theoretical stator angle based on the aerodynamic characteristic change trend in combination with a preset aerodynamic performance optimization algorithm.

[0011] In one embodiment of the present invention, the judgment module includes: a second acquisition unit, a calculation unit and a judgment unit. The second acquisition unit is used to obtain the real-time stator blade angle value of the steam turbine under the current working condition through a sensor. The calculation unit is used to compare the theoretical stator blade angle optimal value with the actual stator blade angle value and calculate the deviation value between the two. The judgment unit is used to judge whether adjustment is required based on the deviation value.

[0012] In a third aspect, the present invention provides an electronic device, comprising:

[0013] at least one processor; and

[0014] a memory communicatively coupled to the at least one processor;

[0015] Wherein, the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent adjustment method of the stator blade angle under the low-load condition of the turbine as described above.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium, including a computer program and instructions. When the computer program or the instructions are run on a computer, the computer executes the method for intelligent adjustment of the stator blade angle under low-load conditions of a steam turbine as described above.

[0017] Compared with the prior art, the method and system for intelligently adjusting the stator blade angle under low-load conditions of a steam turbine according to the present invention have the following beneficial effects:

[0018] 1. The present invention can intelligently adapt to the changes in aerodynamic characteristics of the steam turbine under low-load conditions, accurately calculate the change trend of aerodynamic characteristics under current conditions by real-time acquisition and analysis of the operating data of the steam turbine, and thus realize intelligent adjustment of the stator blade angle;

[0019] 2. By precisely adjusting the angle of the stationary blades, the present invention can effectively improve the operating efficiency and stability of the steam turbine under low load conditions, reduce energy consumption, and extend the life of the equipment;

[0020] 3. The present invention adopts intelligent algorithms and control systems to achieve automatic adjustment of the stationary blade angle, greatly improving the automation and efficiency of the adjustment;

[0021] 4. The present invention establishes a correlation model between flow value, pressure value and temperature value through regression method, and combines with a preset aerodynamic performance optimization algorithm to accurately calculate the optimal value of the theoretical stator blade angle to ensure the accuracy of regulation;

[0022] 5. The present invention can obtain the operation data of the steam turbine in real time, and timely adjust the stator blade angle according to the data changes, so as to achieve real-time optimization of the aerodynamic performance of the steam turbine;

[0023] 6. By intelligently adjusting the angle of the stationary blades, the present invention can reduce the number of failures and repairs of the steam turbine caused by unstable operation, thereby reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a flow chart of a method for intelligently adjusting the stator blade angle of a steam turbine under low-load conditions in the first embodiment of the present invention;

[0025] Figure 2 It is a structural schematic diagram of a stationary blade angle intelligent adjustment system of a steam turbine under low-load conditions in the second embodiment of the present invention;

[0026] Figure 3 It is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention;

[0027] Figure 4 is a schematic cross-sectional structural diagram of a steam turbine in a specific embodiment of the present invention;

[0028] Figure 5 is a partial structural schematic diagram of a steam turbine in a specific embodiment of the present invention;

[0029] Figure 6 It is a schematic diagram of the structure of the stationary blade angle adjustment principle in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0030] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than to limit the embodiments of the present invention. It is also necessary to explain that, for ease of description, only parts related to the embodiments of the present invention are shown in the accompanying drawings, rather than all structures.

[0031] Embodiment 1, Figure 1 : is a flow chart of a method for intelligently adjusting the stator blade angle of a steam turbine under low load conditions in the first embodiment of the present invention, such as Figure 1 As shown, embodiment 1 provides a method for intelligently adjusting the stator blade angle of a steam turbine under low load conditions, including:

[0032] Step S100, acquiring real-time operating data of the steam turbine under low-load conditions, wherein the real-time operating data includes flow parameters, pressure parameters and temperature parameters.

[0033] Specifically, flow parameters may include, for example, the flow rate of steam or gas, which is directly related to the output power and efficiency of the turbine; pressure parameters reflect the pressure state of steam or gas inside the turbine, which is crucial to the stable operation of the turbine; and temperature parameters involve the temperature level of steam or gas, which affects the thermal efficiency and material tolerance of the turbine.

[0034] As a preferred implementation of this embodiment, step S100 includes:

[0035] Step S101, obtaining steam turbine operation data in real time through sensors, wherein the operation data includes flow parameters, pressure parameters and temperature parameters;

[0036] Specifically, flow sensors can be installed at the inlet or outlet of a steam turbine to monitor the flow changes of steam or gas in real time; pressure sensors can be arranged at various pressure levels of a steam turbine to capture pressure fluctuations at different locations; and temperature sensors can be installed at the heat exchanger or steam pipe of a steam turbine to monitor temperature changes. Through the precise measurements of these sensors, the operation data of the steam turbine can be obtained in real time, providing an accurate data basis for the subsequent intelligent adjustment of the stator blade angle.

[0037] Step S102, cleaning the acquired operation data to remove abnormal values ​​and noise, and obtaining the cleaned real-time operation data;

[0038] Specifically, due to sensor failure, data transmission error or environmental interference, the raw data may contain some abnormal values ​​that are obviously deviated from the normal range, or there may be some random noise fluctuations. Through data cleaning, such as statistical methods, filtering technology or machine learning algorithms, these abnormal values ​​and noise can be identified and eliminated to ensure that subsequent aerodynamic characteristics analysis, stator angle optimization calculation, etc. are based on accurate data, thereby improving the reliability and accuracy of the entire stator angle intelligent adjustment system.

[0039] Step S200, calculating the aerodynamic characteristic change trend under the current working condition according to the real-time operating data, and determining the optimal value of the theoretical stator blade angle.

[0040] Specifically, when the steam turbine is running under low load conditions, its parameters such as flow, pressure and temperature will change. The change trend of aerodynamic characteristics can be inferred from the changes in these parameters. For example, a reduction in flow may mean that the stator blade angle needs to be adjusted to maintain efficiency. Based on this change trend, combined with the aerodynamic performance optimization algorithm, the theoretically optimal stator blade angle under the current operating conditions can be calculated, providing a basis for subsequent stator blade angle adjustments.

[0041] As a preferred implementation of this embodiment, step S200 includes:

[0042] Step S201, establishing a correlation model among flow value, pressure value and temperature value by using regression method according to the real-time operation data;

[0043] Specifically, this step is to establish a correlation model between flow values, pressure values ​​and temperature values ​​using regression method based on the real-time operation data after cleaning. Regression method is a statistical method used to determine the quantitative relationship between two or more variables that are interdependent. In this scenario, flow, pressure and temperature are key parameters during turbine operation, and there are complex relationships and influences between them. By establishing a correlation model between these parameters, their changing rules and relationships under different operating conditions can be revealed, thereby providing a basis for subsequent aerodynamic characteristics analysis. For example, when the turbine is operating under low load conditions, the flow may decrease, the pressure may drop, and the temperature may also change. The changes in these parameters are not isolated, but interrelated. By establishing a correlation model, it is possible to analyze how the pressure and temperature will change when the flow decreases, and the impact of this change on the aerodynamic characteristics of the turbine. This analysis helps to understand the changing trend of the aerodynamic characteristics of the turbine under low load conditions and provide a basis for determining the optimal value of the theoretical stator angle. In actual operation, establishing a correlation model requires collecting a large amount of real-time operation data, and preprocessing and cleaning the data to remove outliers and noise. Then, regression analysis methods such as linear regression and multiple regression are used to model parameters such as flow, pressure and temperature. In the modeling process, factors such as nonlinear relationships and hysteresis effects between parameters need to be considered to improve the accuracy and reliability of the model. A good correlation model can be used to predict and analyze the changing trend of the aerodynamic characteristics of the steam turbine under different operating conditions. For example, when the load of the steam turbine changes, the model can be used to predict the changes in parameters such as flow, pressure and temperature, and then infer the changing trend of the aerodynamic characteristics. This prediction and analysis capability is of great significance for the intelligent regulation and optimized operation of the steam turbine.

[0044] Based on the above analysis, this step uses the regression method to establish a correlation model between flow values, pressure values, and temperature values, which provides a basis for subsequent aerodynamic characteristics analysis and stator blade angle optimization. This modeling method not only improves the operating efficiency and stability of the steam turbine under low-load conditions, but also provides strong support for the intelligent regulation and optimized operation of the steam turbine.

[0045] In the preferred implementation of the first embodiment of this invention, the use of regression method to establish the correlation model specifically includes: collecting real-time operating data of the steam turbine under low load conditions, including flow values, pressure values ​​and temperature values; cleaning the data, removing abnormal values ​​and noise, and ensuring the accuracy and reliability of the data. The cleaned data is fitted using the selected regression model. Taking linear regression as an example, the model can be expressed as:

[0046] Y=β 0 +β 1 X 2 +β 2 X 2 +…+β n X n +∈ 1

[0047] Among them, Y is the dependent variable (such as flow value), X 1 ,X 2 ,…,X n is the independent variable (such as pressure value, temperature value), β 0 ,β 1 ,β 2 ,…,β n is the regression coefficient (calculated by optimization methods such as least squares), and ∈ is the error term (representing the part of the variation that the model cannot explain).

[0048] Step S202, calculating the aerodynamic change under the current working condition through the correlation model to obtain the aerodynamic characteristic change trend;

[0049] Specifically, this step is to calculate the aerodynamic change under the current working condition by using the correlation model between the flow value, pressure value and temperature value established by the regression method in step S201. This correlation model is established based on a large amount of real-time operation data, which can reflect the interaction and influence between parameters such as flow, pressure and temperature of the steam turbine under different working conditions. By inputting the current real-time operation data, the model can output the corresponding aerodynamic change, such as the rate of change of flow, the amount of change of pressure or the trend of change of temperature. For example, when the steam turbine transitions from full load to low load, the flow may decrease, the pressure may decrease, and the temperature may also decrease. These changes are not isolated, but interrelated. Through the correlation model, the current flow, pressure and temperature values ​​can be input, and the model will calculate the aerodynamic change based on these input values, such as how much percentage the flow is reduced, how many Pascals the pressure is reduced, how many degrees the temperature is reduced, etc. These changes together constitute the aerodynamic characteristic change trend of the steam turbine under the current working condition. After obtaining the aerodynamic characteristic change trend, the influence of this trend on the operating efficiency and stability of the steam turbine can be further analyzed. For example, a decrease in flow rate may lead to a decrease in turbine output power, a decrease in pressure may affect the internal flow field distribution of the turbine, and a decrease in temperature may affect the thermal efficiency of the turbine. For example, under a low load condition, the real-time operating data is: Flow rate: X 1 =100kg / s, pressure: X 2 =1MPa, temperature: X 3 =500°C, these data are substituted into the correlation model to calculate the aerodynamic change Y. For example, the model may predict a 2% drop in efficiency. Based on this calculation result, it can be concluded that the trend of aerodynamic characteristics change is a decrease in efficiency, so it may be necessary to adjust the stator angle to optimize aerodynamic performance.

[0050] Based on the above analysis, this step calculates the aerodynamic change under the current working conditions through the correlation model, and obtains the trend of aerodynamic characteristics change, which provides an important basis for determining the optimal value of the theoretical stator blade angle and judging whether the stator blade angle needs to be adjusted. This analysis method based on real-time operation data and correlation models not only improves the operating efficiency and stability of the steam turbine under low-load conditions, but also provides strong support for the intelligent adjustment and optimized operation of the steam turbine.

[0051] Step S203, determining the optimal value of the theoretical stator blade angle according to the aerodynamic characteristic change trend and in combination with a preset aerodynamic performance optimization algorithm;

[0052] Specifically, the aerodynamic characteristics change trend reflects the dynamic change of the internal aerodynamic performance of the steam turbine when it is running at low load, which is an important basis for the subsequent adjustment of the stator blade angle. Combined with the preset aerodynamic performance optimization algorithm, this step takes the aerodynamic characteristics change trend as input, and obtains the theoretical optimal value of the stator blade angle under the current working condition through calculation and analysis of the algorithm. This optimal value is obtained based on the comprehensive consideration of the aerodynamic performance optimization algorithm on the operating efficiency, stability and energy consumption of the steam turbine. The aerodynamic performance optimization algorithm may include a variety of mathematical models and optimization strategies, such as genetic algorithms, particle swarm optimization algorithms, etc. These algorithms can intelligently search and find the optimal stator blade angle according to the specific operating data and aerodynamic characteristics of the steam turbine. Assume that the steam turbine is under a low load condition, and the operating data obtained in real time by the sensor show that the flow rate decreases, the pressure drops, and the temperature changes. After cleaning and processing, these data are input into the correlation model, and the model calculates the aerodynamic characteristics change trend under the current working condition, indicating that the efficiency of the steam turbine has decreased and the stability has also been affected. At this time, the aerodynamic performance optimization algorithm will start searching for the stator blade angle that can maximize the efficiency and stability of the steam turbine based on this change trend, combined with the optimization strategy and constraints within the algorithm. After a series of calculations and iterations, the algorithm finally determines a theoretical optimal value for the stator blade angle, which is the target value for subsequent stator blade angle adjustments. Among them, the trend of aerodynamic characteristics changes can be represented by a comprehensive indicator C, which may be the weighted sum of flow, pressure and temperature changes, that is, C = w1 ΔQ+ w2 ΔP+ w3 ΔT, where ΔQ, ΔP, and ΔT are the changes in flow, pressure, and temperature, respectively. w1 , w2 , w3 is the corresponding weight. The aerodynamic performance optimization algorithm uses a genetic algorithm (GA) to find the stator blade angle that optimizes the performance of the steam turbine. Define the objective function f(θ), where θ is the stator blade angle. The objective function may include comprehensive considerations of efficiency, stability, energy consumption, and other aspects, such as:

[0053] f(θ)=η(θ)-λ 1 σ(θ)-λ 2 E(θ)

[0054] Where η(θ) is the efficiency of the turbine, σ(θ) is a measure of stability, E(θ) is the energy consumption, and λ 1 and λ 2is the weight coefficient. Use the selected genetic algorithm to maximize the objective function f(θ). The algorithm iteratively searches the space of stator blade angles to find the value of θ that maximizes f(θ). For example, under a certain low-load condition, the aerodynamic characteristic change trend index C is calculated to be -0.5 (indicating a decrease in performance). Using a genetic algorithm for optimization, the objective function is defined as f(θ) = η(θ) - 0.1σ(θ) - 0.2E(θ). After 100 iterations, the algorithm finds the stator blade angle θ = 30 degrees that maximizes f(θ). Therefore, the theoretical optimal value of the stator blade angle is 30 degrees.

[0055] Based on the above analysis, it can be seen that the embodiment of the present invention can intelligently adapt to the changes in aerodynamic characteristics under low-load conditions and achieve precise adjustment of the stator blade angle, thereby effectively improving the operating efficiency and stability of the steam turbine under low-load conditions. This method not only avoids the inefficiency and inaccuracy of traditional manual adjustment, but also realizes real-time optimization and adjustment of the aerodynamic performance of the steam turbine through intelligent means.

[0056] Step S300, comparing the deviation between the theoretical optimal value and the actual stator blade angle value to determine whether adjustment is required;

[0057] Specifically, by comparing the optimal value of the stator blade angle obtained by theoretical calculation with the stator blade angle value currently in operation of the turbine, it is evaluated whether the aerodynamic performance of the turbine is in the optimal state, and based on this, it is decided whether the stator blade angle needs to be adjusted.

[0058] As a preferred implementation of this embodiment, step S300 includes:

[0059] Step S301, obtaining a real-time stator blade angle value of the steam turbine under the current working condition through a sensor;

[0060] Specifically, these sensors are arranged in positions that can accurately reflect the changes in the stator blade angles, and they can capture the angle information of the stator blades in real time and accurately. When the steam turbine is operating under low-load conditions, its internal aerodynamic characteristics will change, and the angle of the stator blades will be adjusted accordingly to maintain the efficient and stable operation of the steam turbine. The role of the sensor is to monitor these changes in real time and transmit the real-time data of the stator blade angle to the control system. The importance of obtaining real-time stator blade angle data is that it is the basis for determining whether the stator blade angle needs to be adjusted. For example, when the steam turbine is operating under a low-load condition, the sensor monitors in real time that the actual stator blade angle of the steam turbine is 28 degrees.

[0061] Step S302, comparing the theoretical optimal value of the stator blade angle with the actual stator blade angle value, and calculating a deviation value between the two;

[0062] Specifically, the theoretical optimal value of the stator blade angle is calculated based on the real-time operating data (including flow parameters, pressure parameters and temperature parameters) of the steam turbine under low-load conditions, through the analysis of the trend of aerodynamic characteristics changes and the preset aerodynamic performance optimization algorithm. This optimal value represents the stator blade angle that can theoretically achieve the optimal operating efficiency and stability of the steam turbine under the current operating conditions. The actual stator blade angle value is the stator blade angle value of the steam turbine under the current operating conditions obtained in real time by the sensor, which reflects the stator blade angle state of the steam turbine during the current actual operation. By comparing the theoretical optimal value with the actual value, the deviation value between the two can be calculated, and this deviation value directly reflects the degree of difference between the current stator blade angle of the steam turbine and the theoretical optimal value. For example, under a low-load condition, the optimal value of the stator blade angle obtained by theoretical calculation is 30 degrees, while the actual stator blade angle value of the steam turbine obtained in real time by the sensor is 28 degrees. Then, the deviation value between the two is 2 degrees. This deviation value indicates that there is a 2-degree difference between the current stator blade angle of the steam turbine and the theoretical optimal value, which may affect the operating efficiency and stability of the steam turbine. Therefore, the calculation results of this step are crucial for subsequent judgment and adjustment.

[0063] Step S303, based on the deviation value, determine whether the value needs to be adjusted;

[0064] Specifically, if the deviation value is small, it means that the stator blade angle of the steam turbine is close to the optimal value, and the aerodynamic performance is relatively good. At this time, the stator blade angle may not need to be adjusted. However, if the deviation value is large and exceeds the preset threshold, it means that there is a large difference between the stator blade angle of the steam turbine and the optimal value, and the aerodynamic performance may be affected, resulting in a decrease in operating efficiency or poor stability. In this case, it is necessary to make a judgment based on the deviation value whether adjustment is needed. If the deviation value exceeds the preset threshold, it means that the stator blade angle of the steam turbine needs to be adjusted to optimize the aerodynamic performance. For example, the steam turbine is operating under a low-load condition, and the actual stator blade angle value obtained in real time by the sensor is 28 degrees, while the theoretical stator blade angle optimal value calculated based on the real-time operating data is 30 degrees. At this time, the calculated deviation value is 2 degrees. If the preset threshold is 1 degree, then the deviation value of 2 degrees exceeds the threshold, indicating that the stator blade angle of the steam turbine needs to be adjusted.

[0065] Step S400, if the deviation exceeds a preset threshold, the stationary blade angle adjustment mechanism is started to generate an adjustment instruction;

[0066] Specifically, the preset threshold is determined based on factors such as the turbine design parameters, operating experience, and aerodynamic performance optimization algorithm. It represents a maximum deviation range between the actual stator blade angle and the theoretical optimal value. When the actual deviation exceeds this range, it means that the current stator blade angle of the turbine can no longer adapt well to the current low-load condition and needs to be adjusted to optimize the aerodynamic performance. Once the deviation exceeds the preset threshold, the system will start the stator blade angle adjustment mechanism. That is, the system will generate an adjustment instruction, which contains the specific value of adjusting the stator blade angle. This instruction will then be input into the actuator, and the actuator will adjust the stator blade angle to the target angle according to the requirements of the instruction. Through such an intelligent adjustment process, the turbine can maintain efficient and stable operation under low-load conditions, thereby improving its overall performance and reliability. Assuming that the turbine is operating under a low-load condition, the operating data obtained in real time by the sensor and the calculation analysis show that the theoretical optimal value of the stator blade angle is 30 degrees. However, the actual stator blade angle value is 28 degrees, with a deviation of 2 degrees. If the preset threshold is 1 degree, then this deviation exceeds the preset threshold. At this time, the system will start the stator blade angle adjustment mechanism and generate an adjustment instruction, requiring the stator blade angle to be adjusted to 30 degrees.

[0067] Step S500, inputting the adjustment instruction to the actuator to adjust the stator blade angle value to a target angle;

[0068] Specifically, the adjustment instruction is input into the actuator, which is the core component of the turbine stator blade angle adjustment system. It is responsible for driving the stator blades to adjust the angle according to the received instructions. For example, the turbine is operating under a low-load condition. The theoretical optimal value of the stator blade angle has been calculated to be 30 degrees through the previous steps, while the current actual stator blade angle is 28 degrees, and the deviation exceeds the preset threshold. At this time, the system will generate an adjustment instruction to adjust the stator blade angle to 30 degrees. After this instruction is input into the actuator, the actuator starts working and drives the stator blades to adjust the angle. Finally, the stator blade angle is accurately adjusted to 30 degrees, thereby optimizing the aerodynamic performance of the turbine under low-load conditions.

[0069] In a specific embodiment, in a specific embodiment, the actuator is installed on the steam turbine, such as Figure 4As shown, the steam turbine includes a steam turbine shaft pump 1, a shaft pump impeller 2, a cylinder 3 and a plurality of steam turbine stator blades 5. The actuator includes an angle adjustment wheel 4, an angle adjustment translational magnetic plate 6 and an angle adjustment drive mechanism 7. The shaft system impeller 2 is mounted on the steam turbine shaft system 1. The steam turbine shaft system 1 and the shaft system impeller 2 are mounted in the cylinder. The plurality of steam turbine stator blades 5 are respectively arranged in the cylinder, and the tops 52 of the plurality of steam turbine stator blades 5 extend out of the cylinder. The integrated angle adjustment wheel 4 is arranged outside the cylinder, and the interior of the integrated angle adjustment wheel 4 is adapted to correspond to the plurality of steam turbine stator blades 5. The angle adjustment translational magnetic plate 6 is arranged outside the integrated angle adjustment wheel 4, and the angle adjustment translational magnetic plate 6 is used to adapt to correspond to the exterior of the integrated angle adjustment wheel 4. And the angle adjustment driving mechanism 7 is connected to the angle adjustment translational magnetic plate 6 in transmission, and the angle adjustment driving mechanism 7 is used to drive the angle adjustment translational magnetic plate 6 to translate horizontally to the left and right, thereby driving the integrated angle adjustment wheel 4 to rotate in a small angle, and then driving the multiple turbine stator blades 5 to rotate from the first position to the second position 51. Among them, the angle adjustment translational magnetic plate 6 has a translational magnetic strip 61 near the outer side of the integrated angle adjustment wheel 4, and the translational magnetic strip 61 is used to adapt to the integrated angle adjustment wheel 4. Among them, the actuator also includes a connecting rod 71, and the two ends of the connecting rod 71 are respectively connected to the angle adjustment driving mechanism 7 and the angle adjustment translational magnetic plate 6 in transmission. Among them, the outer side of the integrated angle adjustment wheel 4 has an external meshing magnetic wheel 41, and the external meshing magnetic wheel 41 is used to adapt to the translational magnetic strip 61. The inner side of the integrated angle adjustment wheel 4 has an inner meshing magnetic wheel 42, and the inner meshing magnetic wheel 42 is used to correspond to the multiple steam turbine stator blades 5. The tops 52 of the multiple steam turbine stator blades 5 each have a stator blade rotating magnetic wheel 53, and the stator blade rotating magnetic wheel 53 is used to correspond to the inner meshing magnetic wheel 42. The angle adjustment drive mechanism 7 is driven by hydraulic or stepper motor. The turbine shaft system 1 and the shaft system wheel disc 2 are integrally formed.

[0070] In actual applications, the aerodynamic design of the turbine's stator blades, moving blades, etc. is generally performed according to the optimal efficiency under rated power and full load conditions. When operating under rated power and full load conditions, the stator blade angle is at the original design angle θ1 (first position). For different low-load bias conditions, different stator blade optimization angles θ2 (second position 51) can be obtained based on analysis and design. When the steam turbine is in a certain low-load bias condition, the stator blades are adjusted according to the corresponding designed optimization angle. The angle adjustment drive mechanism 7 utilizes the connecting rod 71 to drive the angle adjustment translational magnetic plate 6 to translate horizontally to the left and right. The translational magnetic strip 61 drives the external meshing magnetic wheel 41 to move, thereby driving the integrated angle adjustment wheel 4 to make a circular rotation within a small angle range (such as Figure 5 The integrated angle adjustment wheel 4 has an internal meshing magnetic wheel 42, which can mesh with the stator rotating magnetic wheel 53 at the top 52 of the turbine stator blade 5, driving the top 52 of the stator blade to rotate, and then driving the turbine stator blade 5 to rotate from the original position (first position) to the second position 51, thereby achieving the adjustment of the stator blade angle (as shown in FIG. Figure 6 As shown). Among them, the angle adjustment drive mechanism 7 can be driven by hydraulic drive or stepper motor drive. Among them, taking the angle adjustment drive mechanism 7 driven by a stepper motor as an example, for example, the current turbine stator angle is 28 degrees, the theoretical optimal angle calculated by the system is 30 degrees, and the deviation exceeds the preset threshold. At this time, the system generates an adjustment instruction, requiring the stator angle to be adjusted to 30 degrees. After the actuator receives the instruction, the control logic calculates the number of steps that the stepper motor needs to rotate to drive the angle adjustment translation magnetic plate 6 to translate. The stepper motor starts to rotate, driving the angle adjustment translation magnetic plate 6 to translate to the left a certain distance. The translation magnetic strip 61 interacts with the external meshing magnetic wheel 41, driving the integrated angle adjustment wheel 4 to rotate clockwise by a small angle. The internal meshing magnetic wheel 42 inside the integrated angle adjustment wheel 4 meshes with the stator rotating magnetic wheel 53, driving the stator to rotate clockwise, adjusting from 28 degrees to 30 degrees.

[0071] Embodiment 2: Figure 2 : is a structural schematic diagram of a stationary blade angle intelligent adjustment system for a steam turbine under low load conditions in Embodiment 2 of the present invention. Figure 2As shown, embodiment 2 provides an intelligent stator blade angle adjustment system under low-load conditions of a steam turbine, including: an acquisition module 201, a determination module 202, a judgment module 203, a generation module 204 and an adjustment module 205. The acquisition module 201 is used to obtain real-time operating data of the steam turbine under low-load conditions, wherein the real-time operating data includes flow parameters, pressure parameters and temperature parameters. The determination module 202 is used to calculate the aerodynamic characteristics change trend under the current conditions according to the real-time operating data, and determine the theoretical stator blade angle optimal value. The judgment module 203 is used to compare the deviation between the theoretical optimal value and the actual stator blade angle value to determine whether adjustment is required. The generation module 204 is used to start the stator blade angle adjustment mechanism and generate an adjustment instruction if the deviation exceeds a preset threshold. The adjustment module 205 is used to input the adjustment instruction into the actuator to adjust the stator blade angle value to a target angle.

[0072] In one embodiment of the present invention, the acquisition module 201 includes: a first acquisition unit and a first obtaining unit. The first acquisition unit is used to obtain steam turbine operation data in real time through a sensor, and the operation data includes flow parameters, pressure parameters and temperature parameters. The first obtaining unit is used to clean the acquired operation data, remove abnormal values ​​and noise, and obtain the cleaned real-time operation data.

[0073] In one embodiment of the present invention, the determination module 202 includes: an establishment unit, a second obtaining unit and a determination unit. The establishment unit is used to establish a correlation model between flow values, pressure values ​​and temperature values ​​using a regression method based on the real-time operation data. The second obtaining unit is used to calculate the aerodynamic change under the current working conditions through the correlation model to obtain the aerodynamic characteristic change trend. The determination unit is used to determine the optimal value of the theoretical stator angle based on the aerodynamic characteristic change trend in combination with a preset aerodynamic performance optimization algorithm.

[0074] In one embodiment of the present invention, the judgment module 203 includes: a second acquisition unit, a calculation unit and a judgment unit. The second acquisition unit is used to obtain the real-time stator blade angle value of the steam turbine under the current working condition through a sensor. The calculation unit is used to compare the theoretical stator blade angle optimal value with the actual stator blade angle value and calculate the deviation value between the two. The judgment unit is used to judge whether adjustment is required based on the deviation value.

[0075] The various variations and specific examples of the intelligent adjustment method for the stator blade angle under low-load conditions of a steam turbine provided in Example 1 are also applicable to the intelligent adjustment system for the stator blade angle under low-load conditions of a steam turbine provided in this example. Through the above detailed description of the intelligent adjustment method for the stator blade angle under low-load conditions of a steam turbine, those skilled in the art can clearly know the implementation method of the intelligent adjustment system for the stator blade angle under low-load conditions of a steam turbine in this example. Therefore, for the sake of brevity of the specification, it will not be described in detail here.

[0076] Embodiment 3, Figure 3 is a schematic diagram of the structure of an electronic device in Embodiment 3 of the present invention, such as Figure 3 As shown, the third embodiment further provides an electronic device 300 , which may include: a processor 301 and a memory 302 .

[0077] The memory 302 is used to store programs; the memory 302 may include volatile memory (English: volatile memory), such as random-access memory (English: random-access memory, abbreviated: RAM), such as static random-access memory (English: static random-access memory, abbreviated: SRAM), double data rate synchronous dynamic random access memory (English: Double Data Rate Synchronous Dynamic Random Access Memory, abbreviated: DDR SDRAM), etc.; the memory may also include non-volatile memory (English: non-volatile memory), such as flash memory (English: flash memory). The memory 302 is used to store computer programs (such as applications, functional modules, etc. that implement the above method), computer instructions, etc., and the above computer programs, computer instructions, etc. can be partitioned and stored in one or more memories 302. And the above computer programs, computer instructions, data, etc. can be called by the processor 301.

[0078] The above-mentioned computer programs, computer instructions, etc. may be stored in partitions in one or more memories 302 . And the above-mentioned computer programs, computer instructions, etc. may be called by the processor 301 .

[0079] The processor 301 is used to execute the computer program stored in the memory 302 to implement each step of the method involved in the above embodiment.

[0080] For details, please refer to the relevant description in the previous method embodiment.

[0081] The processor 301 and the memory 302 may be independent structures or integrated structures. When the processor 301 and the memory 302 are independent structures, the memory 302 and the processor 301 may be coupled and connected via a bus 303 .

[0082] The electronic device of this embodiment can execute the technical solution in the above method, and its specific implementation process and technical principle are the same, which will not be repeated here.

[0083] Embodiment 4: Embodiment 4 also provides a computer-readable storage medium, including a computer program and instructions. When the computer program or instructions are executed on a computer, the computer executes the method for intelligently adjusting the stator blade angle under low-load conditions of a steam turbine of any embodiment of the present invention.

[0084] Computer-readable storage media include: USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks, and other media that can store program codes.

[0085] This embodiment also provides a computer program product, which includes: a computer program, which is stored in a readable storage medium. At least one processor of an electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program so that the electronic device executes the solution provided by any of the above embodiments.

[0086] It should be understood that the various forms of the above-described processes may be used to reorder, add or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially or in a different order.

[0087] As long as the expected results of the technical solution disclosed in the present invention can be achieved, this document does not impose any limitations here.

[0088] In summary, the method and system for intelligently adjusting the stator blade angle under low-load conditions of a steam turbine of the present invention have the following beneficial effects:

[0089] 1. The present invention can intelligently adapt to the changes in aerodynamic characteristics of the steam turbine under low-load conditions, accurately calculate the change trend of aerodynamic characteristics under current conditions by real-time acquisition and analysis of the operating data of the steam turbine, and thus realize intelligent adjustment of the stator blade angle;

[0090] 2. By precisely adjusting the angle of the stationary blades, the present invention can effectively improve the operating efficiency and stability of the steam turbine under low load conditions, reduce energy consumption, and extend the life of the equipment;

[0091] 3. The present invention adopts intelligent algorithms and control systems to achieve automatic adjustment of the stationary blade angle, greatly improving the automation and efficiency of the adjustment;

[0092] 4. The present invention establishes a correlation model between flow value, pressure value and temperature value through regression method, and combines with a preset aerodynamic performance optimization algorithm to accurately calculate the optimal value of the theoretical stator blade angle to ensure the accuracy of regulation;

[0093] 5. The present invention can obtain the operation data of the steam turbine in real time, and timely adjust the stator blade angle according to the data changes, so as to achieve real-time optimization of the aerodynamic performance of the steam turbine;

[0094] 6. By intelligently adjusting the angle of the stationary blades, the present invention can reduce the number of failures and repairs of the steam turbine caused by unstable operation, thereby reducing maintenance costs.

[0095] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for intelligently adjusting the stator blade angle of a steam turbine under low-load conditions, characterized in that: include: Acquiring real-time operating data of the steam turbine under low-load conditions, wherein the real-time operating data includes flow parameters, pressure parameters and temperature parameters; According to the real-time operation data, the aerodynamic characteristic change trend under the current working condition is calculated to determine the optimal value of the theoretical stator blade angle; Compare the deviation between the theoretical optimal value and the actual stator blade angle value to determine whether adjustment is needed; If the deviation exceeds a preset threshold, the stationary blade angle adjustment mechanism is activated to generate an adjustment instruction; The adjustment command is input into the actuator to adjust the stator blade angle value to a target angle.

2. The method for intelligently adjusting the stator blade angle of a steam turbine under low load conditions according to claim 1, characterized in that: The real-time operation data of the steam turbine under low load conditions is obtained, wherein the real-time operation data includes flow parameters, pressure parameters and temperature parameters, including: Acquiring steam turbine operating data in real time through sensors, wherein the operating data includes flow parameters, pressure parameters and temperature parameters; The acquired operation data is cleaned to remove abnormal values ​​and noise, so as to obtain the cleaned real-time operation data.

3. The method for intelligently adjusting the stator blade angle of a steam turbine under low load conditions according to claim 1, characterized in that: Calculating the aerodynamic characteristic change trend under the current working condition based on the real-time operation data and determining the optimal value of the theoretical stator blade angle includes: According to the real-time operation data, a correlation model among flow value, pressure value and temperature value is established by using regression method; By using the correlation model, the aerodynamic change under the current working condition is calculated to obtain the aerodynamic characteristic change trend; According to the aerodynamic characteristic variation trend and in combination with a preset aerodynamic performance optimization algorithm, the optimal value of the theoretical stator blade angle is determined.

4. The method for intelligently adjusting the stator blade angle of a steam turbine under low load conditions according to claim 1, characterized in that: The comparison of the deviation between the theoretical optimal value and the actual stator blade angle value to determine whether adjustment is required includes: The real-time stator blade angle value of the steam turbine under the current working condition is obtained through the sensor; Comparing the theoretical optimal value of the stator blade angle with the actual stator blade angle value, and calculating a deviation value between the two; Based on the deviation value, it is determined whether adjustment is required.

5. An intelligent adjustment system for the stator blade angle of a steam turbine under low load conditions, characterized in that: include: An acquisition module, used for acquiring real-time operation data of the steam turbine under low load conditions, wherein the real-time operation data includes flow parameters, pressure parameters and temperature parameters; A determination module, used to calculate the aerodynamic characteristic change trend under the current working condition according to the real-time operation data, and determine the optimal value of the theoretical stator blade angle; A judgment module, used to compare the deviation between the theoretical optimal value and the actual stator blade angle value, and judge whether adjustment is needed; a generating module, configured to start a stator blade angle adjustment mechanism and generate an adjustment instruction if the deviation exceeds a preset threshold; and The regulating module is used to input the regulating instruction to the actuator to adjust the stator blade angle value to a target angle.

6. The intelligent stator blade angle adjustment system for a steam turbine under low load conditions according to claim 5, characterized in that: The acquisition module comprises: A first acquisition unit, used for acquiring steam turbine operation data in real time through a sensor, wherein the operation data includes flow parameters, pressure parameters and temperature parameters; The first obtaining unit is used to clean the acquired operation data, remove abnormal values ​​and noise, and obtain the cleaned real-time operation data.

7. The intelligent stator blade angle adjustment system for a steam turbine under low load conditions according to claim 5, characterized in that: The determination module comprises: An establishing unit, used to establish a correlation model between flow value, pressure value and temperature value by using regression method according to the real-time operation data; A second obtaining unit is used to calculate the aerodynamic change amount under the current working condition through the correlation model to obtain the aerodynamic characteristic change trend; The determination unit is used to determine the optimal value of the theoretical stator blade angle according to the change trend of the aerodynamic characteristics in combination with a preset aerodynamic performance optimization algorithm.

8. The intelligent stator blade angle adjustment system for a steam turbine under low load conditions according to claim 5, characterized in that: The judging module comprises: A second acquisition unit is used to acquire a real-time stator blade angle value of the steam turbine under the current working condition through a sensor; a calculation unit, used for comparing the theoretical optimal value of the stator blade angle with the actual stator blade angle value, and calculating a deviation value between the two; A judging unit is used to judge whether adjustment is needed based on the deviation value.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively coupled to the at least one processor; Wherein, the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the intelligent adjustment method of the stator blade angle under the low-load condition of the turbine as described in any one of claims 1-4.

10. A computer-readable storage medium, characterized in that: The method comprises a computer program and instructions. When the computer program or the instructions are executed on a computer, the computer is enabled to execute the method for intelligently adjusting the stator blade angle under low-load conditions of a steam turbine as described in any one of claims 1 to 4.

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