Intelligent adjusting method and system for angle of stator blade of steam turbine

Abstract

The invention discloses an intelligent adjustment method and system for the angle of a stator blade of a steam turbine, and the method comprises the steps: obtaining a power difference value between a current power value of the steam turbine and a preset full power threshold value, and determining whether the steam turbine is in a low-power operation condition or not according to the power difference value. If the blade is in the low-power operation working condition, the blade surface flow separation strength, the wake area expansion range, the airflow secondary flow enhancement degree and the blade induced attack angle variable quantity are obtained; and inputting the blade surface flow separation intensity, the wake area expansion range, the airflow secondary flow enhancement degree and the blade induced attack angle variation into a pre-established blade cascade aerodynamic loss model to generate a current blade cascade total pressure loss value. Therefore, according to the intelligent adjustment method for the steam turbine stationary blade angle, the stationary blade angle can be adjusted in a self-adaptive mode when the steam turbine operates at low power, pneumatic losses are effectively reduced, and the operation efficiency and stability of the steam turbine under the non-design working condition are improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical fields of energy and power plants, and particularly to an intelligent adjustment method and system for the static blade angle of a steam turbine. Background Art

[0002] A steam turbine is a core device in a power plant, and its aerodynamic design plays a decisive role in the efficiency of the unit. During actual operation, the steam turbine needs to adapt to various load demands, and the full-power and low-power operating conditions alternate continuously. However, the steam turbine is usually designed according to the full-power condition. Under the low-power off-design condition, the aerodynamic characteristics deviate from the design point, the flow-through loss increases, which seriously affects the operating efficiency of the unit.

[0003] When the steam turbine operates at low power, the airflow separation on the blade surface intensifies, the wake region expands, the secondary flow intensity increases, the induced angle of attack increases, and the aerodynamic loss of the cascade rises sharply. At the same time, the leakage flow between the stages of the steam turbine intensifies, the pressure distribution deteriorates, the axial thrust balance is broken, and the vibration of the steam turbine intensifies. In addition, the low-power operation results in uneven pressure on the exhaust surface of the last-stage blade, serious local airflow diffusion, and strong buffeting of the steam turbine, which seriously affects the safe and stable operation.

[0004] Aiming at the aerodynamic characteristic differences under different load demands, it is difficult for traditional steam turbines to balance the performance under full-load and low-power conditions. The static blade angle remains fixed and cannot adapt to the aerodynamic flow-through characteristics under different conditions, resulting in a sharp drop in the efficiency of the steam turbine under low-power conditions. Therefore, it is urgent to develop a variable static blade steam turbine technology to realize the adaptive adjustment of the static blade angle, reduce the aerodynamic loss under low-power conditions, and improve the operating efficiency of the steam turbine. Summary of the Invention

[0005] The embodiments of the present invention provide an intelligent adjustment method and system for the static blade angle of a steam turbine, which can adaptively adjust the static blade angle when the steam turbine operates at low power, effectively reduce the aerodynamic loss, and improve the operating efficiency and stability of the steam turbine under off-design conditions.

[0006] To achieve the above object, in a first aspect, the present invention provides an intelligent adjustment method for the static blade angle of a steam turbine, including: obtaining the power difference between the current power value of the steam turbine and a preset full-power threshold value, and determining whether it is in a low-power operation condition according to the power difference. When in the low-power operation condition, obtaining the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary flow of the air flow, and the change amount of the induced angle of attack of the blade, and inputting the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary flow of the air flow, and the change amount of the induced angle of attack of the blade into a pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade. Judging whether the current total pressure loss value of the cascade exceeds a preset aerodynamic loss threshold value to generate a judgment result, where the judgment result includes a first result and a second result. If the judgment result is the first result, obtaining the current static blade angle and calculating the optimal static blade angle adjustment amount. Inputting the optimal static blade angle adjustment amount into an actuator to adjust the static blade angle to a target angle.

[0007] In an embodiment of the present invention, the obtaining the power difference between the current power value of the steam turbine and a preset full-power threshold value, and determining whether it is in a low-power operation condition according to the power difference includes: obtaining the current power value of the steam turbine through a sensor, calculating the difference between the preset full-power threshold value and the current power value to generate a power difference. Comparing the power difference with a preset low-power threshold value to judge whether it exceeds the low-power threshold value. If the power difference exceeds the preset low-power threshold value, it is preliminarily determined to be in a low-power operation condition. Using a sliding window algorithm to smooth the current power value to eliminate noise interference and generate a stable power value. Recalculating the difference between the stable power value and the preset full-power threshold value to generate a corrected power difference. Judging again according to the corrected power difference whether it exceeds the preset low-power threshold value. If the corrected power difference exceeds the preset low-power threshold value, it is finally determined to be in a low-power operation condition.

[0008] In an embodiment of the present invention, when in the low-power operation condition, obtaining the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary flow of the air flow, and the change amount of the induced angle of attack of the blade, and inputting the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary flow of the air flow, and the change amount of the induced angle of attack of the blade into a pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade includes: obtaining the flow separation intensity on the blade surface and the enhancement degree of the secondary flow of the air flow through a sensor to generate a flow quantity. Calculating the expansion range of the wake region according to the flow quantity and the change amount of the induced angle of the blade. Inputting the flow quantity, the expansion range of the wake region, and the enhancement degree of the secondary flow of the air flow into the pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade.

[0009] In an embodiment of the present invention, when the judgment result is the first result, obtaining the current stator blade angle and calculating the optimal stator blade angle adjustment amount includes: when the judgment result is the first result, obtaining the current stator blade angle. Based on the blade load reduction characteristic and the current stator blade angle, calculating the optimal stator blade angle adjustment amount.

[0010] In an embodiment of the present invention, inputting the optimal stator blade angle adjustment amount into the actuator and adjusting the stator blade angle to the target angle includes: inputting the optimal stator blade angle adjustment amount into the actuator, and the actuator adjusts the stator blade angle value to the target angle. Obtain the difference between the current angle and the target angle of the stator blade, and judge whether the difference meets the preset range. If the difference exceeds the preset range, recalculate the optimal stator blade angle adjustment amount and update the target angle.

[0011] In a second aspect, the present invention provides an intelligent adjustment system for the stator blade angle of a steam turbine, including: a determination module, a first generation module, a second generation module, a calculation module, and an adjustment module. The determination module is used to obtain the power difference between the current power value of the steam turbine and the preset full-power threshold, and determine whether it is in a low-power operating condition according to the power difference. The first generation module is used to obtain the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary air flow, and the change amount of the blade induced angle of attack when in the low-power operating condition, and input the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary air flow, and the change amount of the blade induced angle of attack into a pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade. The second generation module is used to judge whether the current total pressure loss value of the cascade exceeds a preset aerodynamic loss threshold and generate a judgment result, where the judgment result includes a first result and a second result. The calculation module is used to obtain the current stator blade angle and calculate the optimal stator blade angle adjustment amount if the judgment result is the first result. The adjustment module is used to input the optimal stator blade angle adjustment amount into the actuator and adjust the stator blade angle to the target angle.

[0012] In an embodiment of the present invention, the determination module includes: a first generation unit, a first judgment unit, a first determination unit, a second generation unit, a third generation unit, a second judgment unit, and a second determination unit. The first generation unit is configured to obtain the current power value of the steam turbine through a sensor, calculate the difference between a preset full-power threshold and the current power value, and generate a power difference. The first judgment unit is configured to compare the power difference with a preset low-power threshold to determine whether the low-power threshold is exceeded. The first determination unit is configured to preliminarily determine a low-power operating condition if the power difference exceeds the preset low-power threshold. The second generation unit is configured to smooth the current power value by using a sliding window algorithm to eliminate noise interference and generate a stable power value. The third generation unit is configured to recalculate the difference between the stable power value and the preset full-power threshold to generate a corrected power difference. The second judgment unit is configured to determine again whether the corrected power difference exceeds the preset low-power threshold. The second determination unit is configured to finally determine a low-power operating condition if the corrected power difference exceeds the preset low-power threshold.

[0013] In an embodiment of the present invention, the first generation module includes: a fourth generation unit, a first calculation unit, and a fifth generation unit. The fourth generation unit is configured to obtain the flow separation intensity on the blade surface and the enhanced secondary flow intensity of the air flow through a sensor and generate a flow quantity. The first calculation unit is configured to calculate the expanded range of the wake region according to the flow quantity and the change amount of the blade induction angle. The fifth generation unit is configured to input the flow quantity, the expanded range of the wake region, and the enhanced secondary flow intensity of the air flow into the pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade.

[0014] In a third aspect, the present invention provides an electronic device, including:

[0015] at least one processor; and

[0016] a memory communicatively connected to the at least one processor;

[0017] wherein, the memory stores instructions executable 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 for the static blade angle of the steam turbine as described above.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium, including a computer program and instructions, and when the computer program or the instructions are run on a computer, the computer is enabled to execute the intelligent adjustment method for the static blade angle of the steam turbine as described above.

[0019] Compared with the prior art, the intelligent adjustment method and system for the static blade angle of a steam turbine according to the present invention have the following beneficial effects:

[0020] 1. The present invention can adaptively adjust the static blade angle during the low-power operation of the steam turbine, effectively reducing the aerodynamic loss. By intelligently adjusting the static blade angle, the operating efficiency of the steam turbine under off-design conditions (such as low-power conditions) is significantly improved;

[0021] 2. By adjusting the static blade angle, the airflow distribution on the blade surface can be optimized, reducing phenomena such as flow separation on the blade surface, expansion of the wake region, and enhancement of secondary flow of the airflow, thereby reducing the aerodynamic loss of the blade row, reducing the vibration and buffeting of the steam turbine, and improving the operating stability of the steam turbine;

[0022] 3. By reducing the aerodynamic loss and vibration under low-power conditions, the fatigue damage of the steam turbine components can be reduced, thereby extending the service life of the steam turbine;

[0023] 4. The present invention adopts intelligent algorithms and sensor technologies, can monitor the operating state of the steam turbine in real time, and automatically calculate and adjust the static blade angle according to preset thresholds and models, realizing the intelligent and automatic adjustment of the static blade angle of the steam turbine;

[0024] 5. By optimizing the operating efficiency of the steam turbine, the energy utilization rate of the power station can be improved, energy waste can be reduced, and operating costs can be lowered;

[0025] 6. The present invention is applicable to the operation of steam turbines under different load demands, can adaptively adjust the static blade angle to meet the aerodynamic flow characteristics under different working conditions, and improves the adaptability and flexibility of the steam turbine. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a schematic flow chart of an intelligent adjustment method for the static blade angle of a steam turbine in Embodiment 1 of the present invention;

[0027] Figure 2 is a schematic structural diagram of an intelligent adjustment system for the static blade angle of a steam turbine in Embodiment 2 of the present invention;

[0028] Figure 3 is a schematic structural diagram of an electronic device in Embodiment 3 of the present invention;

[0029] Figure 4 is a schematic cross-sectional structural diagram of a steam turbine in a specific embodiment of the present invention;

[0030] Figure 5 is a schematic partial structural diagram of a steam turbine in a specific embodiment of the present invention;

[0031] Figure 6It is a schematic structural diagram of the static blade angle adjustment principle in a specific embodiment of the present invention. Detailed implementation mode

[0032] The following further elaborates on the embodiments of the present invention in conjunction with the accompanying drawings and examples. It can be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than limiting the embodiments of the present invention. Additionally, it should be noted that for the convenience of description, only parts related to the embodiments of the present invention are shown in the drawings, rather than all structures.

[0033] Embodiment 1 Figure 1 It is a schematic flowchart of an intelligent adjustment method for the static blade angle of a steam turbine in Embodiment 1 of the present invention. As Figure 1 shown, Embodiment 1 provides an intelligent adjustment method for the static blade angle of a steam turbine, including:

[0034] Step S100, obtaining the power difference between the current power value of the steam turbine and the preset full-power threshold, and determining whether it is in a low-power operation condition based on the power difference;

[0035] Among them, the step S100 includes:

[0036] Step S101, obtaining the current power value of the steam turbine through a sensor, calculating the difference between the preset full-power threshold and the current power value to generate a power difference;

[0037] Specifically, through a sensor installed on the steam turbine or related system, the current power output value of the steam turbine is captured and obtained in real time. This power value reflects the actual working ability of the steam turbine in the current operating state and is an important parameter for evaluating its operating condition. Subsequently, the system uses a preset full-power threshold, which is determined based on, for example, the design specifications of the steam turbine and the power output at full load operation, representing the maximum power output ability of the steam turbine under ideal conditions. By calculating the difference between the real-time obtained current power value and this preset full-power threshold, the system can generate a power difference. This difference directly reflects the gap between the current power output of the steam turbine and the designed full power and is an important basis for judging whether the steam turbine is in a low-power operation condition. Through this step, the system can accurately and timely grasp the power output state of the steam turbine, providing key data support for subsequent intelligent adjustment strategies such as low-power condition judgment and static blade angle adjustment.

[0038] In a specific example, for instance, the designed full power of a steam turbine is 1000 MW. During actual operation, the current power value of the steam turbine is monitored in real time by a sensor and is 750 MW. At this time, the preset full power threshold is 1000 MW. According to step S101, the formula for calculating the power difference is: Power difference = Preset full power threshold - Current power value; Substituting the specific values into the formula, we get: Power difference = 1000 MW - 750 MW = 250 MW. Therefore, a power difference of 250 MW is generated.

[0039] Step S102, compare the power difference with a preset low power threshold to determine whether it exceeds the low power threshold;

[0040] Specifically, compare the power difference with the preset low power threshold. If the power difference exceeds the low power threshold, then the system preliminarily determines that the steam turbine is in a low power operation condition. This judgment process is crucial for subsequent assessment of aerodynamic losses and adjustment of the stator blade angle because it determines whether to activate the adaptive adjustment mechanism of the stator blade angle to optimize the operation efficiency and stability of the steam turbine under low power conditions.

[0041] In a specific example, for instance, the preset full power threshold of the steam turbine is 1000 MW, and the preset low power threshold is 200 MW (the difference relative to the full power). At a certain moment, the current power value of the steam turbine obtained by the sensor is 750 MW. First, calculate the difference between the current power value and the full power threshold, that is, 1000 MW - 750 MW = 250 MW. Then, compare this power difference of 250 MW with the preset low power threshold of 200 MW. The corresponding algorithm formula can be expressed as: If (Current power value - Full power threshold) < - Low power threshold, then it is judged as exceeding the low power threshold. In this example, since 250 MW > 200 MW, it is judged that the steam turbine is currently in a low power operation condition.

[0042] Step S103, if the power difference exceeds the preset low power threshold, then preliminarily determine it as a low power operation condition;

[0043] Specifically, if the power difference exceeds the low power threshold, it indicates that the current power of the steam turbine is significantly lower than the normal full power operation state. Therefore, it can be preliminarily judged that the steam turbine is in a low power operation condition.

[0044] Step S104, use a sliding window algorithm to smooth the current power value, eliminate noise interference, and generate a stable power value;

[0045] Specifically, the sliding window algorithm smooths data fluctuations and reduces the impact of outliers or noise by averaging or weighted averaging data within a certain range. During the operation of a steam turbine, due to various factors such as sensor accuracy and data transmission errors, the actual power values obtained may have certain fluctuations or noise. These fluctuations or noise may interfere with the accurate judgment of the steam turbine's operating state. Therefore, by smoothing the current power value through the sliding window algorithm, these noise interferences can be effectively eliminated, generating a more accurate and stable power value, providing a reliable data basis for subsequent judgments and decisions. This step is of great significance for ensuring the accuracy and stability of the intelligent adjustment of the steam turbine's stator blade angle.

[0046] In a specific example, for instance, the power values of a steam turbine within a certain period have fluctuations in the measured data due to sensor noise or instantaneous fluctuations, such as: [950MW, 960MW, 940MW, 970MW, 930MW, 980MW, 920MW]. Using these power values directly for judgment may lead to misjudgment because they are affected by noise. At this time, select a sliding window size, say 3. This means considering the average of the last 3 power values to smooth the data. The first window: [950MW, 960MW, 940MW], average = (950 + 960 + 940) / 3 = 950MW. The second window: [960MW, 940MW, 970MW], average = (960 + 940 + 970) / 3 = 956.67MW. The third window: [940MW, 970MW, 930MW], average = (940 + 970 + 930) / 3 = 946.67MW. And so on, calculate the averages of subsequent windows. Through the above sliding window algorithm, a series of more smoothed power values are obtained: [950MW, 956.67MW, 946.67MW,...]. These values are more stable than the original data and reduce the impact of noise. The average calculation of the sliding window algorithm can be expressed as:

[0047]

[0048] where Pj is the original power value at the j-th moment, n is the size of the sliding window, and the stable power value i is the stable power value at the i-th moment after being processed by the sliding window algorithm.

[0049] Through this example, it can be seen how the sliding window algorithm effectively smooths the power value data, eliminates noise interference, and thus generates more stable power values. This helps to more accurately determine whether the steam turbine is operating under low power conditions and provides a reliable data basis for subsequent stator blade angle adjustment.

[0050] Step S105, recalculate the difference by using the stable power value and the preset full power threshold to generate a corrected power difference;

[0051] Specifically, compare the stable power value with the preset full power threshold, and recalculate the difference, that is, the corrected power difference. This corrected power difference can better reflect the gap between the current actual power level of the steam turbine and the full power state, thereby providing a more accurate basis for subsequent judgment on whether the steam turbine is in a low power operation condition. Through such processing, the accuracy and reliability of the entire intelligent regulation method can be improved, ensuring that the steam turbine can timely adjust the static blade angle during low power operation, effectively reduce the aerodynamic loss, and improve the operation efficiency and stability.

[0052] In a specific example, for instance, the preset full power threshold of the steam turbine is 1000 MW, and the stable power value after smoothing processing by the sliding window algorithm is 750 MW. Calculate the corrected power difference: Corrected power difference = preset full power threshold - stable power value (Corrected power difference = 1000 MW - 750 MW = 250 MW). Assume that the preset low power threshold is 20% relative to the full power, that is, 200 MW (based on the full power of 1000 MW). Since the corrected power difference of 250 MW exceeds the preset low power threshold of 200 MW, it can be finally determined as a low power operation condition. Corrected power difference = preset full power threshold - stable power value (that is: ΔP 修正 = P 满功率 - P 稳定 ).

[0053] Where: ΔP 修正 is the corrected power difference, P 满功率 is the preset full power threshold, and P 稳定 is the stable power value after smoothing processing by the sliding window algorithm. In the above example, by applying this formula, the corrected power difference is calculated to be 250 MW, and based on this, it is judged that the steam turbine is in a low power operation condition.

[0054] Step S106, judge again whether the corrected power difference exceeds the preset low power threshold;

[0055] Specifically, this step is carried out after the original current power value is smoothed by the sliding window algorithm to generate a stable power value and the corrected power difference is recalculated with the preset full power threshold. The purpose of this step is to further improve the accuracy of the judgment because the original power value may be affected by noise or instantaneous fluctuations, resulting in the result of the preliminary judgment (step S102) being unreliable. By judging again with the corrected power difference, these interference factors can be effectively filtered out, ensuring that only when the steam turbine is indeed in a low power operation state will the subsequent aerodynamic loss assessment and static blade angle adjustment be carried out.

[0056] Step S107, if the corrected power difference exceeds the preset low power threshold, it is finally determined as the low power operation condition;

[0057] Specifically, if the corrected power difference exceeds the preset low power threshold, it indicates that the steam turbine is indeed in the low power operation state, so it is finally determined as the low power operation condition.

[0058] In a specific embodiment, there is a steam turbine with a designed full power of 1000 MW. During actual operation, due to changes in load demand, the steam turbine may need to operate at different power levels. To achieve intelligent adjustment of the stator blade angle of the steam turbine, it is first necessary to determine whether the steam turbine is in the low power operation condition through a series of steps. The current power value of the steam turbine is obtained in real time through sensors. For example, at a certain moment, the current power value measured by the sensor is 700 MW. A full power threshold is preset, which is the designed full power of the steam turbine, 1000 MW in this case. At the same time, a low power threshold is set, such as 80% of the full power, that is, 800 MW. Then, the difference between the current power value and the full power threshold is calculated, that is, 1000 MW - 700 MW = 300 MW. Next, this power difference is compared with the preset low power threshold (the difference relative to the full power, that is, 200 MW). Since the calculated power difference of 300 MW exceeds the preset low power threshold of 200 MW, it is preliminarily determined that the steam turbine may be in the low power operation condition. However, due to possible noise interference in sensor measurement, it is necessary to smooth the current power value. Here, the sliding window algorithm is used to average the power values within a recent period of time to eliminate noise. For example, after smoothing, the obtained stable power value is still 700 MW. Next, the difference is recalculated using this stable power value of 700 MW and the preset full power threshold of 1000 MW, and the corrected power difference is obtained as 300 MW. The corrected power difference of 300 MW is compared with the preset low power threshold of 200 MW again. Since the corrected power difference still exceeds the low power threshold, the determination that the steam turbine is in the low power operation condition is further confirmed. Finally, it is determined that the steam turbine is currently in the low power operation condition.

[0059] Based on the above analysis, it can be seen that the present invention can accurately determine whether the steam turbine is in the low power operation condition and provide an accurate basis for subsequent stator blade angle adjustment. This intelligent adjustment method can adaptively cope with the aerodynamic characteristic differences under different load demands, effectively improving the operation efficiency and stability of the steam turbine.

[0060] Step S200, when in the low-power operation condition, obtain the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary air flow, and the change amount of the blade induced angle of attack, and input the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary air flow, and the change amount of the blade induced angle of attack into a pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade;

[0061] Among them, the step S200 includes:

[0062] Step S201, obtain the flow separation intensity on the blade surface and the enhancement degree of the secondary air flow through a sensor to generate a flow quantity;

[0063] Step S202, calculate the expansion range of the wake region according to the flow quantity and the change amount of the blade induced angle;

[0064] Step S203, input the flow quantity, the expansion range of the wake region, and the enhancement degree of the secondary air flow into the pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade;

[0065] Specifically, flow separation on the blade surface and secondary air flow are key factors affecting aerodynamic performance. The sensor obtains the flow separation intensity and the enhancement degree of the secondary flow by detecting the pressure distribution on the blade surface and the flow field characteristics. These data reflect the complexity of the fluid motion around the blade and are directly related to energy loss and efficiency. The acquisition of the flow quantity lays the foundation for subsequent analysis. For example, in a high-load condition of a certain turbine blade, the sensor detects that the flow separation intensity near the trailing edge increases by 20%, and the enhancement degree of the secondary flow increases by 15%. These changes indicate that the blade load is too high, which may lead to a decrease in efficiency and an increase in vibration. The change amount of the blade induced angle reflects the deviation between the actual flow and the design condition. When the flow condition changes, the induced angle will be adjusted accordingly, affecting the size of the wake region. For example, an increase in the induced angle by 2 degrees may cause the area of the wake region to expand by 10%, exacerbating energy loss. The cascade aerodynamic loss model is the core tool for analyzing the total pressure loss. This model integrates factors such as the flow quantity, the range of the wake region, and the intensity of the secondary flow, and outputs the current total pressure loss value of the cascade.

[0066] In a specific example, for instance, in a steam turbine, the following data is monitored by sensors: the flow separation intensity on the blade surface: 20%, the enhancement intensity of the secondary air flow: 15%, and the change in the blade induction angle: 3 degrees. The flow separation intensity on the blade surface and the enhancement intensity of the secondary air flow are obtained by sensors to generate a flow quantity. The flow quantity can be simply expressed as a linear combination of these two intensities: flow quantity = the value corresponding to the flow separation intensity + the enhancement intensity of the secondary air flow, that is, flow quantity = 20% + 15% = 35%. Based on the flow quantity and the change in the blade induction angle, the expansion range of the wake region is calculated. Assuming that the expansion range of the wake region is proportional to the flow quantity and the change in the induction angle, it can be expressed by the formula: expansion range of the wake region = K1 * flow quantity + K2 * change in the blade induction angle, where K1 and K2 are empirical coefficients. Assuming K1 = 1.5 and K2 = 2, then: expansion range of the wake region = 1.5 * 35% + 2 * 3 degrees = 0.525 + 6 = 6.525. The flow quantity can be obtained by sensors acquiring the flow separation intensity on the blade surface and the enhancement intensity of the secondary air flow and performing appropriate weighting or combination. The change in the blade induction angle can be obtained by sensors monitoring the difference between the actual induction angle and the designed induction angle of the blade. The flow quantity, the expansion range of the wake region, and the enhancement intensity of the secondary air flow are input into a pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade. For example, the cascade aerodynamic loss model is a multiple linear regression model: current total pressure loss value of the cascade = a * flow quantity + b * expansion range of the wake region + c * enhancement intensity of the secondary air flow, where a, b, and c are model coefficients. Assuming a = 0.1, b = 0.2, and c = 0.05, then: current total pressure loss value of the cascade = 0.1 * 35% + 0.2 * 6.525 + 0.05 * 15% = 0.035 + 1.305 + 0.0075 = 1.3475. Among them, the cascade aerodynamic loss model can be, for example, a multiple linear regression model. In a multiple linear regression model, the coefficients of each input parameter (such as a, b, c, etc.) need to be determined. These coefficients can be obtained through training with experimental data or simulation data. Use a set of experimental data or simulation data under different working conditions to train the model. The data should include the flow separation intensity on the blade surface, the enhancement intensity of the secondary air flow, the change in the blade induction angle, and the corresponding total pressure loss value of the cascade. By minimizing the error between the model prediction value and the true value, the parameters of the model are adjusted so that the model can accurately predict the total pressure loss value of the cascade under different working conditions. Use another set of independent experimental data or simulation data to verify the trained model. By comparing the difference between the model prediction value and the true value, the accuracy and reliability of the model are evaluated. If the difference is within an acceptable range, the model is considered valid.

[0067] Step S300, determine whether the current total pressure loss value of the cascade exceeds a preset aerodynamic loss threshold, and generate a judgment result, where the judgment result includes a first result and a second result;

[0068] Specifically, the system will preset a pneumatic loss threshold, which is determined based on the steam turbine design specifications, historical operation data, and pneumatic performance optimization goals, and represents the maximum pneumatic loss level that the steam turbine can accept under normal operating conditions. Subsequently, the total pressure loss value of the current cascade calculated by the cascade pneumatic loss model is compared with this preset threshold. The comparison result will generate two possible judgment results: the first result and the second result. The first result means that the current total pressure loss value of the cascade exceeds the preset pneumatic loss threshold, indicating that the pneumatic performance of the steam turbine under the current low-power operating condition has been significantly affected, the pneumatic loss is too large, which may lead to problems such as efficiency decline and vibration intensification. The second result is that the current total pressure loss value of the cascade does not exceed the preset threshold, indicating that the pneumatic performance of the steam turbine under the current condition is still within the acceptable range, and there is no need to adjust the stator blade angle. The judgment result of this step is crucial for subsequent operations because it directly determines whether to activate the adaptive adjustment mechanism of the stator blade angle to optimize the operating efficiency and stability of the steam turbine. If the judgment result is the first result, that is, the pneumatic loss is too large, step S400 will be entered.

[0069] Step S400, if the judgment result is the first result, obtain the current stator blade angle and calculate the optimal stator blade angle adjustment amount, where the first result is that the current total pressure loss value of the cascade exceeds the preset pneumatic loss threshold;

[0070] Among them, step S400 includes:

[0071] Step S401, if the judgment result is the first result, obtain the current stator blade angle;

[0072] Step S402, calculate the optimal stator blade angle adjustment amount based on the blade load reduction characteristic and the current stator blade angle;

[0073] Specifically, when the judgment result is the first result, that is, the current total pressure loss value of the cascade exceeds the preset pneumatic loss threshold, the system enters the calculation process of stator blade angle adjustment. First, obtain the current stator blade angle. This step is necessary because the adjustment of the stator blade angle is based on the current angle, and understanding the current stator blade angle is the basis for calculating the optimal adjustment amount. Then, based on the blade load reduction characteristic and the current stator blade angle, calculate the optimal stator blade angle adjustment amount. The blade load reduction characteristic refers to how the pneumatic load borne by the blade changes at different stator blade angles. This characteristic is obtained in advance through experiments or calculations and is used as the basis for adjusting the stator blade angle. By considering this characteristic and the current stator blade angle, an optimal stator blade angle adjustment amount can be calculated, which can optimize the pneumatic performance of the blade under the low-power operating condition, reduce the pneumatic loss, and improve the operating efficiency and stability of the steam turbine.

[0074] In a specific example, for instance, a certain steam turbine is currently operating under a low-power condition. Through sensors and a cascade aerodynamic loss model, it is calculated that the current total pressure loss value of the cascade has exceeded the preset aerodynamic loss threshold. At this time, first, the current stator vane angle is obtained through the sensor. Assume the current stator vane angle is 30 degrees. Next, it is necessary to calculate the optimal stator vane angle adjustment amount based on the blade load reduction characteristic and the current stator vane angle. The blade load reduction characteristic is usually obtained through experiments or simulations, which describes how the aerodynamic load borne by the stator vane changes when the stator vane angle changes. Assume this characteristic can be represented by a simple linear relationship: for every 1-degree increase in the stator vane angle, the blade load decreases by 2%. According to the current aerodynamic loss situation and the blade load reduction characteristic, it is determined that a certain amount of blade load needs to be reduced to reduce the aerodynamic loss. Assume the system calculates that the blade load needs to be reduced by 10%. Then, according to the blade load reduction characteristic (for every 1-degree increase in the stator vane angle, the load decreases by 2%), the system can calculate that a 5-degree increase in the stator vane angle is required to achieve the goal of reducing the blade load by 10%. Therefore, the optimal stator vane angle adjustment amount is +5 degrees. The system inputs the calculated optimal stator vane angle adjustment amount (+5 degrees) into the actuator. The actuator adjusts the stator vane angle from 30 degrees to 35 degrees according to the received instruction. Among them, the optimal stator vane angle adjustment amount = (target load reduction percentage / load percentage reduced per degree of stator vane angle) * current stator vane angle adjustment direction (positive or negative). Among them, the target load reduction percentage is determined according to the current aerodynamic loss situation and the optimization goal, the load percentage reduced per degree of stator vane angle is the blade load reduction characteristic parameter obtained through experiments or simulations, and the current stator vane angle adjustment direction is determined according to whether the stator vane angle needs to be increased or decreased actually (positive means increase, negative means decrease).

[0075] Step S500: Input the optimal stator vane angle adjustment amount into the actuator to adjust the stator vane angle to the target angle;

[0076] Among them, step S500 includes:

[0077] Step S501: Input the optimal stator vane angle adjustment amount into the actuator, and the actuator adjusts the stator vane angle value to the target angle;

[0078] Step S502: Obtain the difference between the current angle and the target angle of the stator vane, and determine whether the difference meets the preset range;

[0079] Step S503: If the difference exceeds the preset range, recalculate the optimal stator vane angle adjustment amount and update the target angle;

[0080] Specifically, first, the optimal static blade angle adjustment amount is input into the actuator, and the actuator then adjusts the static blade angle to the preset target angle according to the received instruction. This step is crucial for realizing the intelligent adjustment of the static blade angle. It directly converts the optimization result calculated by the algorithm into actual mechanical actions, thereby adjusting the aerodynamic characteristics of the steam turbine. Next, the difference between the current angle and the target angle of the static blade is obtained. This is to verify whether the adjustment effect of the actuator is accurate. By comparing the actually adjusted static blade angle with the target angle, the accuracy and reliability of the adjustment process can be evaluated. If the difference is within the preset range, it indicates that the adjustment process is successful, and the static blade angle has approached or reached the optimal state, which helps to reduce aerodynamic losses. However, if it is found that the difference exceeds the preset range, it means that the adjustment of the actuator may be interfered by some factors or there are errors, and the static blade angle cannot be accurately adjusted to the target value. In this case, the system needs to recalculate the optimal static blade angle adjustment amount and update the target angle. This feedback mechanism ensures the accuracy and adaptability of the static blade angle adjustment. Even in the case of adjustment errors, through recalculation and adjustment, the static blade angle can be made as close to the optimal state as possible, thereby effectively reducing aerodynamic losses and improving the operating efficiency of the steam turbine.

[0081] In a specific example, for instance, when a certain steam turbine is operating under the current low-power condition, the optimal adjustment amount of the static blade angle calculated through the cascade aerodynamic loss model is +3 degrees (that is, the current static blade angle needs to be increased by 3 degrees to reach the optimal state). The system inputs this optimal adjustment amount of +3 degrees of the static blade angle into the actuator. After receiving the instruction, the actuator starts to adjust the static blade angle, with the goal of increasing the static blade angle by 3 degrees. After the adjustment is completed, the system obtains the current angle (assumed to be 42 degrees) and the target angle (the original angle of 42 degrees + the adjustment amount of 3 degrees = 45 degrees) of the static blade. Calculate the difference between the current angle and the target angle: 45 degrees - 42 degrees = 3 degrees (ideally, it should be 0 degrees, indicating that the adjustment is in place). Determine whether this difference is within the preset range (for example, the preset range is ±0.5 degrees). In this example, the difference of 3 degrees exceeds the preset range. Since the difference exceeds the preset range, the system believes that the initial adjustment of the actuator has not achieved the expected effect, and there may be adjustment errors or interferences. Therefore, the system needs to recalculate the optimal adjustment amount of the static blade angle. Considering the error of the initial adjustment, the system may adjust the calculation strategy based on the magnitude and direction of the error as well as historical adjustment data to more accurately estimate the new adjustment amount. Assume that after recalculation, the system obtains a new optimal adjustment amount of the static blade angle of +3.2 degrees (considering possible systematic errors or lags in the initial adjustment). The system updates the target angle to the original angle of 42 degrees + the new adjustment amount of 3.2 degrees = 45.2 degrees. Repeat steps S501 and S502: The system inputs the new optimal adjustment amount of +3.2 degrees of the static blade angle into the actuator, and the actuator adjusts the static blade angle again. After the adjustment is completed, the system obtains the current angle (assumed to be 45.1 degrees this time) and the target angle (45.2 degrees) of the static blade again. Calculate the difference between the current angle and the target angle: 45.2 degrees - 45.1 degrees = 0.1 degree, and this difference is within the preset range (±0.5 degrees). Since the difference is within the preset range, the system believes that the static blade angle has been successfully adjusted to be close to the optimal state, and the adjustment process ends.

[0082] Based on the above analysis, it can be seen that the present invention forms a closed-loop control system. By real-time monitoring and adjusting the static blade angle, it ensures the efficient and stable operation of the steam turbine under different loads. This intelligent adjustment method not only improves the adaptability of the steam turbine but also extends the service life of the steam turbine components, reduces the operating cost, and improves the energy utilization rate by reducing the aerodynamic loss. In addition, the automation and intelligence characteristics of the present invention reduce manual intervention, improve the accuracy and response speed of the adjustment, and provide strong support for the intelligent operation of the steam turbine.

[0083] 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 disk 2, a cylinder 3, and multiple steam turbine stationary blades 5. The actuator includes an angle adjustment runner 4, an angle adjustment translation gear plate 6, and an angle adjustment drive unit 7. The shaft pump disk 2 is installed on the steam turbine shaft pump 1. The steam turbine shaft pump 1 and the shaft pump disk 2 are installed inside the cylinder. The multiple steam turbine stationary blades 5 are respectively arranged inside the cylinder, and the tops 52 of the multiple steam turbine stationary blades 5 extend out of the cylinder. The angle adjustment runner 4 is arranged outside the cylinder, and the inside of the angle adjustment runner 4 corresponds and adapts to the multiple steam turbine stationary blades 5. The angle adjustment translation gear plate 6 is arranged outside the angle adjustment runner, and the angle adjustment translation gear plate 6 is used to correspond and adapt to the outside of the angle adjustment runner 4. The angle adjustment drive unit 7 is in transmission connection with the angle adjustment translation gear plate 6, and the angle adjustment drive unit 7 is used to drive the angle adjustment translation gear plate 6 to perform left - right translation in the horizontal direction, thereby driving the angle adjustment runner 4 to perform a small - angle circular rotation, and further driving the multiple steam turbine stationary blades 5 to rotate from the first position to the second position 51. Among them, when the angle adjustment drive unit 7 receives the optimal stationary blade angle adjustment amount, it transmits the driving force to the angle adjustment translation gear plate 6 through the connecting rod 71. The gear plate makes left - right translation in the horizontal direction under the push of the connecting rod 71. The translation gear 61 on the translation gear plate 6 meshes with the external meshing rotating gear 41 on the angle adjustment runner 4. As the translation gear plate 6 translates, the external meshing rotating gear 41 drives the angle adjustment runner 4 to perform a small - angle circular rotation. The internal meshing rotating gear 42 inside the angle adjustment runner 4 meshes with the stationary blade rotating gear 53 at the top 52 of the steam turbine stationary blade 5. When the angle adjustment runner 4 rotates, it drives the stationary blade rotating gear 53 to rotate through the internal meshing rotating gear 42, thereby realizing the angle adjustment of the steam turbine stationary blade 5. Among them, the angle adjustment translation gear plate 6 has a translation gear 61 near the outer side of the angle adjustment runner 4, and the translation gear 61 is used to correspond and adapt to the angle adjustment runner 4. Among them, the outer side of the angle adjustment runner 4 has an external meshing rotating gear 41, and the external meshing rotating gear 41 is used to correspond and adapt to the translation gear 61. Among them, the inner side of the angle adjustment runner 4 has an internal meshing rotating gear 42, and the internal meshing rotating gear 42 is used to correspond and adapt to the multiple steam turbine stationary blades 5. Among them, the tops 52 of the multiple steam turbine stationary blades 5 all have stationary blade rotating gears 53, and the stationary blade rotating gears 53 are used to correspond and adapt to the internal meshing rotating gear 42.

[0084] In practical applications, steam turbines are generally aerodynamically designed for the optimal efficiency under the full-load condition of the rated power. When operating under the full-load condition of the rated power, the angle of the stationary blade 5 of the steam turbine is at the original design angle θ1 (the first position). For different low-load off-design conditions, different optimal stationary blade optimization angles θ2 (the second position 51) can be obtained according to the analysis and design. When the steam turbine is in a certain low-load off-design condition, the stationary blade is adjusted according to the corresponding designed optimization angle. The angle adjustment drive unit 7 uses the connecting rod 71 to drive the angle adjustment translation gear plate 6 to move horizontally left and right. The translation gear 61 drives the external meshing rotating gear 41 to act, thereby driving the integrated angle adjustment runner 4 to perform a small-angle circular rotation (as Figure 5 shown). There is an internal meshing rotating gear 42 inside the integrated angle adjustment runner 4, which can mesh with the stationary blade rotating gear 53 at the top 52 of the stationary blade 5 of the steam turbine, driving the rotation of the structure at the top 52 of the stationary blade, and further driving the stationary blade 5 of the steam turbine to rotate from the original position (the first position) to the second position 51, thereby realizing the adjustment of the stationary blade angle (as Figure 6 shown). The angle of the moving blade is fixed and not adjusted. Only by adjusting the angle of the stationary blade 5 of the steam turbine to match the angle of the moving blade can the overall aerodynamic performance be optimized.

[0085] Embodiment 2, Figure 2 is a schematic structural diagram of an intelligent adjustment system for the angle of the stationary blade of a steam turbine in Embodiment 2 of the present invention. As Figure 2 shown, Embodiment 2 provides an intelligent adjustment system for the angle of the stationary blade of a steam turbine, including: a determination module 201, a first generation module 202, a second generation module 203, a calculation module 204, and an adjustment module 205. The determination module 201 is used to obtain the power difference between the current power value of the steam turbine and the preset full-power threshold, and determine whether it is in a low-power operating condition according to the power difference. The first generation module 202 is used to, when in the low-power operating condition, obtain the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary flow of the air flow, and the change amount of the induced angle of attack of the blade, and input the flow separation intensity on the blade surface, the expansion range of the wake region, the enhancement degree of the secondary flow of the air flow, and the change amount of the induced angle of attack of the blade into a pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade. The second generation module 203 is used to judge whether the current total pressure loss value of the cascade exceeds the preset aerodynamic loss threshold, and generate a judgment result, where the judgment result includes a first result and a second result. The calculation module 204 is used to, if the judgment result is the first result, obtain the current stationary blade angle and calculate the optimal stationary blade angle adjustment amount. The adjustment module 205 is used to input the optimal stationary blade angle adjustment amount into the actuator to adjust the stationary blade angle to the target angle.

[0086] In this embodiment, the determination module 201 includes: a first generation unit, a first judgment unit, a first determination unit, a second generation unit, a third generation unit, a second judgment unit, and a second determination unit. The first generation unit is configured to obtain the current power value of the steam turbine through a sensor, calculate the difference between a preset full power threshold and the current power value, and generate a power difference. The first judgment unit is configured to compare the power difference with a preset low power threshold to determine whether the low power threshold is exceeded. The first determination unit is configured to preliminarily determine a low power operation condition if the power difference exceeds the preset low power threshold. The second generation unit is configured to perform a smoothing process on the current power value by using a sliding window algorithm to eliminate noise interference and generate a stable power value. The third generation unit is configured to recalculate the difference between the stable power value and the preset full power threshold to generate a corrected power difference. The second judgment unit is configured to determine again whether the corrected power difference exceeds the preset low power threshold. The second determination unit is configured to finally determine a low power operation condition if the corrected power difference exceeds the preset low power threshold.

[0087] In this embodiment, the first generation module 202 includes: a fourth generation unit, a first calculation unit, and a fifth generation unit. The fourth generation unit is configured to obtain the flow separation intensity on the blade surface and the secondary flow enhancement degree of the air flow through a sensor and generate a flow rate. The first calculation unit is configured to calculate the expansion range of the wake area according to the flow rate and the change amount of the blade induction angle. The fifth generation unit is configured to input the flow rate, the expansion range of the wake area, and the secondary flow enhancement degree of the air flow into the pre-established cascade aerodynamic loss model to generate the current total pressure loss value of the cascade.

[0088] In this embodiment, the calculation module 204 includes an acquisition unit and a second calculation unit. The acquisition unit is configured to obtain the current stator blade angle if the judgment result is the first result. The second calculation unit is configured to calculate the optimal stator blade angle adjustment amount based on the blade load reduction characteristic and the current stator blade angle.

[0089] In this embodiment, the adjustment module 205 includes: an input unit, a third judgment unit, and an update unit. The input unit is configured to input the optimal stator blade angle adjustment amount into the actuator, and the actuator adjusts the stator blade angle value to the target angle. The third judgment unit is configured to obtain the difference between the current stator blade angle and the target angle and determine whether the difference meets a preset range. The update unit is configured to recalculate the optimal stator blade angle adjustment amount and update the target angle if the difference exceeds the preset range.

[0090] The various variations and specific examples of the intelligent adjustment method for the steam turbine stator blade angle provided in the first embodiment are equally applicable to the intelligent adjustment system for the steam turbine stator blade angle provided in this embodiment. Through the detailed description of an intelligent adjustment method for the steam turbine stator blade angle mentioned above, those skilled in the art can clearly know the implementation manner of the intelligent adjustment system for the steam turbine stator blade angle in this embodiment. Therefore, for the sake of brevity of the specification, it will not be elaborated here.

[0091] Embodiment 3 Figure 3 is a schematic structural diagram of an electronic device in Embodiment 3 of the present invention. As Figure 3 shown, Embodiment 3 also provides an electronic device 300, which may include: a processor 301 and a memory 302.

[0092] The memory 302 is used to store programs; the memory 302 may include a volatile memory (English: volatile memory), such as a random access memory (English: random-access memory, abbreviation: RAM), such as a static random access memory (English: static random-access memory, abbreviation: SRAM), a double data rate synchronous dynamic random access memory (English: Double Data Rate Synchronous Dynamic Random Access Memory, abbreviation: DDR SDRAM), etc.; the memory may also include a non-volatile memory (English: non-volatile memory), such as a flash memory (English: flash memory). The memory 302 is used to store computer programs (such as application programs and functional modules for implementing the above methods), computer instructions, etc. The above computer programs, computer instructions, etc. may be stored in one or more memories 302 in a partitioned manner. And the above computer programs, computer instructions, data, etc. may be called by the processor 301.

[0093] The above computer programs, computer instructions, etc. may be stored in one or more memories 302 in a partitioned manner. And the above computer programs, computer data, etc. may be called by the processor 301.

[0094] The processor 301 is used to execute the computer programs stored in the memory 302 to implement each step in the methods involved in the above embodiments.

[0095] Specifically, reference may be made to the relevant descriptions in the foregoing method embodiments.

[0096] The processor 301 and the memory 302 can be independent structures or integrated structures integrated together. When the processor 301 and the memory 302 are independent structures, the memory 302 and the processor 301 can be coupled through the bus 303.

[0097] The electronic device in this embodiment can execute the technical solutions in the above method. The specific implementation process and technical principle are the same and will not be elaborated here.

[0098] Embodiment 4 also provides a computer-readable storage medium, including a computer program and instructions. When the computer program or instructions run on a computer, the computer is enabled to execute the intelligent adjustment method for the static blade angle of the steam turbine according to any embodiment of the present invention.

[0099] The computer-readable storage medium includes various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0100] This embodiment also provides a computer program product. The computer program product includes a computer program. The computer program is stored in a readable storage medium. At least one processor of the electronic device can read the computer program from the readable storage medium, and at least one processor executes the computer program to enable the electronic device to execute the solution provided in any of the above embodiments.

[0101] It should be understood that various forms of the processes shown above can be used, reordering, adding, or deleting steps. For example, the steps recorded in the disclosure of the present invention can be executed in parallel, sequentially, or in a different order.

[0102] As long as the desired results of the technical solutions disclosed in the present invention can be achieved, no limitations are imposed herein.

[0103] In summary, the intelligent adjustment method and system for the static blade angle of the steam turbine of the present invention have the following beneficial effects:

[0104] 1. The present invention can adaptively adjust the static blade angle during the low-power operation of the steam turbine, effectively reducing the aerodynamic loss. By intelligently adjusting the static blade angle, the operation efficiency of the steam turbine under off-design conditions (such as low-power conditions) is significantly improved.

[0105] 2. By adjusting the static blade angle, the airflow distribution on the blade surface can be optimized, reducing phenomena such as flow separation on the blade surface, expansion of the wake region, and enhancement of secondary flow of the airflow, thereby reducing the aerodynamic loss of the cascade, reducing the vibration and buffeting of the steam turbine, and improving the operation stability of the steam turbine.

[0106] 3. By reducing the aerodynamic loss and vibration under low-power conditions, the fatigue damage of the steam turbine components can be reduced, thereby extending the service life of the steam turbine.

[0107] 4. The present invention adopts intelligent algorithms and sensor technologies, can monitor the operating state of the steam turbine in real time, and automatically calculates and adjusts the angle of the stationary blade according to preset thresholds and models, realizing the intelligent and automatic adjustment of the angle of the stationary blade of the steam turbine;

[0108] 5. By optimizing the operating efficiency of the steam turbine, the energy utilization rate of the power station can be improved, energy waste can be reduced, and operating costs can be lowered;

[0109] 6. The present invention is applicable to the operation of steam turbines under different load demands, can adaptively adjust the angle of the stationary blade to meet the aerodynamic flow characteristics under different working conditions, and improves the adaptability and flexibility of the steam turbine.

[0110] Note that the above are only the preferred embodiments of the present invention and the applied technical principles. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope 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 only. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. An intelligent adjustment method for the angle of a steam turbine stator blade, characterized in that: include: Obtaining a power difference between a current power value of the steam turbine and a preset full power threshold, and determining whether the turbine is in a low power operating condition according to the power difference; If the low-power operating condition is in the condition, the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary flow of the airflow, and the change in the blade induced angle of attack are obtained, and the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary flow of the airflow, and the change in the blade induced angle of attack are input into a pre-established cascade aerodynamic loss model to generate a current cascade total pressure loss value; Determine whether the current blade cascade total pressure loss value exceeds a preset aerodynamic loss threshold, and generate a determination result, wherein the determination result includes a first result and a second result; If the judgment result is the first result, the current stator blade angle is obtained, and the optimal stator blade angle adjustment amount is calculated; The optimal stator blade angle adjustment amount is input into the actuator to adjust the stator blade angle to the target angle.

2. The intelligent adjustment method for the turbine stator blade angle according to claim 1, characterized in that: The obtaining of the power difference between the current power value of the steam turbine and the preset full power threshold, and determining whether the turbine is in a low power operating condition according to the power difference comprises: The current power value of the steam turbine is obtained through the sensor, and the difference between the preset full power threshold and the current power value is calculated to generate a power difference value; Comparing the power difference with a preset low power threshold, determining whether the low power threshold is exceeded; If the power difference exceeds the preset low power threshold, it is preliminarily determined as a low power operating condition; The current power value is smoothed by using a sliding window algorithm to eliminate noise interference and generate a stable power value; Recalculating the difference between the stable power value and the preset full power threshold to generate a corrected power difference; Determining again whether the corrected power difference exceeds the preset low power threshold; If the corrected power difference exceeds the preset low power threshold, it is ultimately determined as a low power operating condition.

3. The intelligent adjustment method for the turbine stator blade angle according to claim 1, characterized in that: If the low-power operation condition is in the condition, the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary flow of the airflow, and the change in the blade induced angle of attack are obtained, and the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary flow of the airflow, and the change in the blade induced angle of attack are input into a pre-established cascade aerodynamic loss model to generate the current cascade total pressure loss value, including: The flow separation intensity on the blade surface and the secondary flow enhancement degree of the airflow are acquired through sensors to generate flow quantity; Calculating the expansion range of the wake area according to the flow amount and the change in the blade induction angle; The flow rate, the expansion range of the wake area and the secondary flow enhancement degree of the airflow are input into the pre-established blade cascade aerodynamic loss model to generate the current blade cascade total pressure loss value.

4. The intelligent adjustment method for the turbine stator blade angle according to claim 1, characterized in that: If the judgment result is the first result, obtaining the current stator blade angle and calculating the optimal stator blade angle adjustment amount includes: If the judgment result is the first result, obtaining the current stator blade angle; The optimum stator blade angle adjustment amount is calculated based on the blade load reduction characteristic and the current stator blade angle.

5. The intelligent adjustment method for the turbine stator blade angle according to claim 1, characterized in that: Inputting the optimal stator blade angle adjustment amount into the actuator to adjust the stator blade angle to the target angle includes: The optimal stator blade angle adjustment amount is input into the actuator, and the actuator adjusts the stator blade angle value to a target angle; Obtain the difference between the current angle of the stator blade and the target angle, and determine whether the difference is within the preset range; If the difference exceeds the preset range, the optimal stator blade angle adjustment amount is recalculated and the target angle is updated.

6. An intelligent adjustment system for the angle of a steam turbine stator blade, characterized in that: include: A determination module, used to obtain a power difference between a current power value of the steam turbine and a preset full power threshold, and determine whether it is in a low power operating condition according to the power difference; A first generating module is used for obtaining the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary flow of the airflow and the change amount of the blade induced angle of attack when the blade is in the low-power operating condition, and inputting the flow separation intensity on the blade surface, the expansion range of the wake area, the enhancement degree of the secondary flow of the airflow and the change amount of the blade induced angle of attack into a pre-established cascade aerodynamic loss model to generate a current cascade total pressure loss value; A second generating module, configured to determine whether the current blade cascade total pressure loss value exceeds a preset aerodynamic loss threshold, and generate a determination result, wherein the determination result includes a first result and a second result; a calculation module, configured to obtain the current stator blade angle and calculate the optimal stator blade angle adjustment amount if the judgment result is the first result; The regulating module is used to input the optimal stator blade angle adjustment amount into the actuator to adjust the stator blade angle to a target angle.

7. The intelligent adjustment system for the turbine stator blade angle according to claim 6, characterized in that: The determination module comprises: A first generating unit is used to obtain a current power value of the steam turbine through a sensor, perform a difference calculation between a preset full power threshold and the current power value, and generate a power difference value; A first judging unit, configured to compare the power difference with a preset low power threshold to judge whether the power difference exceeds the low power threshold; A first determining unit, configured to preliminarily determine a low-power operating condition if the power difference exceeds the preset low-power threshold; A second generating unit is used to use a sliding window algorithm to smooth the current power value, eliminate noise interference, and generate a stable power value; A third generating unit, configured to recalculate a difference between the stable power value and the preset full power threshold value to generate a corrected power difference value; A second judgment unit, used for judging again whether the preset low power threshold is exceeded according to the corrected power difference; The second determination unit is used to finally determine the low-power operating condition if the corrected power difference exceeds the preset low-power threshold.

8. The intelligent adjustment system for the turbine stator blade angle according to claim 6, characterized in that: The first generation module comprises: A fourth generating unit, configured to obtain the flow separation intensity on the blade surface and the secondary flow enhancement degree of the airflow through a sensor to generate a flow quantity; A first calculation unit is used to calculate the expansion range of the wake area according to the flow amount and the change amount of the blade induction angle; The fifth generating unit is used to input the flow rate, the expansion range of the wake area and the secondary flow enhancement degree of the airflow into the pre-established aerodynamic loss model of the blade cascade to generate the current blade cascade total pressure loss 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 executable 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 for the turbine stator blade angle according to any one of claims 1-5.

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 run on a computer, the computer is enabled to execute the intelligent adjustment method for the turbine stator blade angle according to any one of claims 1 to 5.

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