Method for calculating aerodynamic performance of fan blade and terminal

Abstract

The application provides a method and a terminal for calculating aerodynamic performance of a fan blade. The method comprises: obtaining a transition point parameter on the fan blade; inputting the transition point parameter as a boundary constraint condition into an aerodynamic simulation model to calculate blade airfoil aerodynamic coefficients in a first angle of attack range; and obtaining blade airfoil aerodynamic performance data through an extrapolation model according to the blade airfoil aerodynamic coefficients in the first angle of attack range. The application uses the transition point as an erosion proxy parameter and combines simulation and extrapolation, so that complete airfoil aerodynamic performance data in a full angle of attack range can be quickly and accurately obtained without constructing a complex erosion geometry.

Description

Technical Field

[0001] This invention relates to the field of wind turbine technology, and in particular to a method and terminal for calculating the aerodynamic performance of wind turbine blades. Background Technology

[0002] During long-term operation, wind turbine blades are subjected to impacts from rainwater, dust, and other particulate matter, making their leading edges susceptible to erosion damage. This alters the boundary layer state of the airfoil surface, and accurately assessing its impact on aerodynamic performance is crucial for power generation loss assessment and operation and maintenance decisions. Using Computational Fluid Dynamics (CFD) requires establishing complex erosion geometry models, which are time-consuming for modeling and mesh generation. Wind tunnel experiments are costly, time-consuming, and struggle to reproduce field Reynolds numbers. The equivalent roughness method ignores changes in the leading-edge geometry and has poor universality. Calculating the aerodynamic performance of wind turbine blades by directly simulating the physical morphology of erosion is computationally complex, resulting in low computational efficiency. Summary of the Invention

[0003] The technical problem to be solved by the present invention is to provide a method and terminal for calculating the aerodynamic performance of wind turbine blades, which can quickly, efficiently and accurately calculate the leading edge erosion aerodynamic performance of wind turbine blades.

[0004] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A method for calculating the aerodynamic performance of a wind turbine blade includes: Obtain the parameters of the turning point on the wind turbine blades; The transition point parameters are input as boundary constraints into the aerodynamic simulation model to calculate the airfoil aerodynamic coefficients within the first angle of attack range. Based on the aerodynamic coefficients of the airfoil within the first angle of attack range, the aerodynamic performance data of the airfoil are obtained through an extrapolation model.

[0005] To solve the above-mentioned technical problems, another technical solution adopted by the present invention is as follows: A terminal for calculating the aerodynamic performance of a wind turbine blade includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned method for calculating the aerodynamic performance of a wind turbine blade.

[0006] The beneficial effects of this invention are as follows: By obtaining the transition point parameters on the wind turbine blades and using the transition point (the boundary between laminar and turbulent flow) as the erosion characterization parameter, the complex and varied erosion geometry is eliminated, and the multi-form and irregular leading-edge erosion is simplified into a single, measurable transition point parameter, which greatly reduces the modeling difficulty and parameter complexity. The transition point parameters are input as boundary constraints into the aerodynamic simulation model to calculate the aerodynamic coefficients of the airfoil within the first angle of attack range. By directly substituting the transition point as the boundary constraint into the aerodynamic simulation, there is no need to reconstruct the erosion geometry or perform fine mesh generation, which significantly shortens the simulation calculation time and improves the efficiency of aerodynamic coefficient acquisition. By combining the simulation within the first angle of attack range with the extrapolation model to extend to the full angle of attack range, while ensuring the calculation accuracy at small angles of attack, the aerodynamic performance coverage under all operating conditions is achieved. This enables the rapid, efficient, and accurate calculation of the aerodynamic performance of the leading-edge erosion of wind turbine blades, solving the problems of complex modeling, long cycle, and poor versatility of traditional methods. Attached Figure Description

[0007] Figure 1 This is a flowchart illustrating a method for calculating the aerodynamic performance of a wind turbine blade according to an embodiment of the present invention. Figure 2 The lift coefficient of a wind turbine blade varies with the angle of attack in a method for calculating the aerodynamic performance of a wind turbine blade according to an embodiment of the present invention. Figure 3 This is another flowchart of a method for calculating the aerodynamic performance of a wind turbine blade according to an embodiment of the present invention; Figure 4 A diagram of the transition region of a wind turbine blade, illustrating a method for calculating the aerodynamic performance of a wind turbine blade according to an embodiment of the present invention. Figure 5 This is a diagram of the laminar and turbulent flow boundary point of a method for calculating the aerodynamic performance of a wind turbine blade according to an embodiment of the present invention. Figure 6 A comparison diagram of airfoil aerodynamic coefficient curves for a wind turbine blade aerodynamic performance calculation method according to an embodiment of the present invention; Figure 7 A power curve comparison diagram of a method for calculating the aerodynamic performance of a wind turbine blade according to an embodiment of the present invention; Figure 8 This is a schematic diagram of an aerodynamic performance calculation terminal for a wind turbine blade according to an embodiment of the present invention. Detailed Implementation

[0008] Definitions:

[0009] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0010] In existing technologies, wind turbine blades are prone to erosion damage such as leading-edge pitting, cracking, and coating peeling during long-term operation, leading to aerodynamic performance degradation and reduced power generation. Current aerodynamic performance assessment methods require detailed geometric modeling of the erosion morphology, which is cumbersome, involves complex meshes, and requires significant computation. Furthermore, these methods lack versatility across different damage morphologies, making large-scale engineering applications difficult. Meanwhile, infrared thermal imaging is widely used in the field for rapid detection of the blade boundary layer transition location. However, this detection data is only used for qualitative assessment of the damage degree and lacks standardized quantitative methods. This results in problems such as a disconnect between field detection data and simulation calculations, complex erosion modeling, low computational efficiency, and poor universality, making it impossible to quickly and accurately assess the aerodynamic performance and power generation loss of eroded blades under all operating conditions.

[0011] To at least address the aforementioned issues, the "transition point" (the boundary between laminar and turbulent flow) on the wind turbine blades was first located and its data recorded. This data was then input into aerodynamic simulation software as constraints to calculate the aerodynamic parameters of the wind turbine blades within a specific angular range. Finally, an extrapolation model was used to extend these aerodynamic parameters within this specific angular range to all possible angles during wind turbine operation, yielding complete blade aerodynamic performance data. In this way, the transition point can be used as an erosion proxy parameter, combined with simulation and extrapolation, to quickly and accurately obtain complete airfoil aerodynamic performance data across the entire angle of attack range without the need to construct complex erosion geometry.

[0012] The following describes in detail a method for calculating the aerodynamic performance of a wind turbine blade according to the present invention. Please refer to [link / reference]. Figure 1 The method 100 includes steps 110 to 130: Step 110: Obtain the turning point parameters on the wind turbine blades.

[0013] In one optional implementation, infrared thermal imaging technology is used to detect the wind turbine blades, acquiring images of the blade surface temperature distribution. Based on the temperature jump characteristics of the transition region, the suction and pressure transition points of each section of the blade airfoil are identified. Combined with the blade airfoil chord length, the transition point parameters (chord length percentage) are calculated. For example, at the blade section r / R=0.7 (where r is the distance between the blade position and the blade root, and R is the blade length), the chord length percentage of the suction transition point is 10%, and the chord length percentage of the pressure transition point is 15%.

[0014] Step 120: Input the transition point parameters as boundary constraints into the aerodynamic simulation model and calculate the blade airfoil aerodynamic coefficient within the first angle of attack range.

[0015] In one optional implementation, the first angle of attack range is selected as... ∈[ [10°, 20°], the transition point parameters (10% chord length of suction surface, 15% chord length of pressure surface) obtained in step 110 are used as boundary constraints and input into CFD simulation software (such as Fluent software). The Transition SST(4eqn) turbulence model is adopted. The transition point position is specified by writing a UDF file. The lift coefficient (C1), drag coefficient (Cd) and pitching moment coefficient (Cm) corresponding to each angle of attack within the angle of attack range are calculated to obtain the blade airfoil aerodynamic coefficient within the first angle of attack range.

[0016] Step 130: Obtain the aerodynamic performance data of the blade airfoil by extrapolation model based on the aerodynamic coefficient of the blade airfoil within the first angle of attack range.

[0017] In one alternative implementation, the result calculated in step 120 is... ∈[ Aerodynamic coefficients within the range of 10°, 20° are input into the Viterna extrapolation model, with the extrapolation target range set to the full angle of attack range. ∈[ [180°, 180°], the angle of attack step size is consistent with the step size of the first angle of attack range (e.g., 1° / step), and the aerodynamic coefficients are obtained through extrapolation calculations across the entire angle of attack range. The aerodynamic coefficients of the first angle of attack range are integrated with those of the entire angle of attack range, and the aerodynamic coefficients of the corresponding angle of attack intervals within the entire angle of attack range are replaced to obtain complete blade airfoil aerodynamic performance data.

[0018] As described above, obtaining the transition point parameter simplifies the characterization of wind turbine blade leading-edge erosion, transforming the multi-form, irregular erosion problem into a single measurable parameter. By combining the aerodynamic simulation model and the extrapolation model, the aerodynamic coefficients at small angles of attack are calculated based on the transition point. The obtained aerodynamic coefficient results are then extrapolated to the full angle of attack using the model to obtain the aerodynamic coefficient simulation results. This approach achieves rapid acquisition of airfoil aerodynamic performance data while ensuring computational accuracy, solving the technical problems of computational complexity and low efficiency.

[0019] In one embodiment of the present invention, step 110 includes steps 111 to 113.

[0020] Step 111: Use infrared thermal imaging technology to acquire surface temperature distribution images of the wind turbine blades.

[0021] In one optional implementation, an infrared thermal imager is used to photograph the wind turbine blades, ultimately obtaining an image of the temperature distribution on the blade surface (including the suction and pressure surfaces). Using thermal measurement methods such as infrared thermal imaging, temperature-sensitive paint spraying, and surface thermal film sensor bonding, the surface temperature difference between laminar and turbulent flow states is captured. Based on the thermal field distribution characteristics, image processing and temperature field analysis are used to identify transition boundaries. Surface pulsation pressure measurement involves acquiring the time-domain signal of pressure pulsation in the near-wall region of the boundary layer, converting it into sound pressure level gradient characteristics through spectral analysis, and determining the flow transition boundary based on the pressure pulsation intensity and spectral gradient changes.

[0022] Step 112: Based on the temperature jump characteristics of the transition region of the wind turbine blade, the suction surface transition point and pressure surface transition point of the blade airfoil are identified from the surface temperature distribution image.

[0023] In one optional implementation, the acquired temperature distribution image is processed using an image processing algorithm (such as a threshold segmentation algorithm), a temperature jump threshold is set, and the boundary position of the temperature jump is identified. This boundary position is the transition point. The suction surface transition point and pressure surface transition point of each section of the airfoil (e.g., r / R=0.3, 0.5, 0.7, 0.9) are marked respectively. For example, for the section with r / R=0.7, the suction surface transition point is located 150 mm from the leading edge of the airfoil, and the pressure surface transition point is located 225 mm from the leading edge of the airfoil.

[0024] Step 113: Obtain the transition point parameters based on the suction surface transition point and the pressure surface transition point.

[0025] In one alternative implementation, the airfoil chord length of the blade at the r / R=0.7 section is measured to be 1500 mm. Based on the ratio of the transition point position to the chord length, the transition point parameter (chord length percentage) is calculated, i.e., the chord length percentage of the transition point on the suction side is 10%, and the chord length percentage of the transition point on the pressure side is 15%. These two chord length percentages are used as the transition point parameter.

[0026] As described above, relying on infrared thermal imaging technology, the location of the transition point of the wind turbine blades can be quickly captured on site without the need for complex measurements of erosion morphology. The transition point is identified through temperature jump characteristics, which has high accuracy and strong adaptability, and reduces the difficulty of obtaining the transition point parameters.

[0027] In one embodiment of the present invention, step 113 includes steps 1131 to 1134.

[0028] Step 1131: Collect the airfoil chord length of the wind turbine blades.

[0029] In one optional implementation, the airfoil chord length of each section of the target blade is measured. For example, for the section with r / R=0.7, the straight-line distance (chord length) from the leading edge to the trailing edge of the airfoil is measured to be 1500 mm, and this chord length data is recorded. At the same time, the chord lengths of other key sections of the blade (such as r / R=0.3, 0.5, 0.9) are measured for subsequent batch calculations.

[0030] Step 1132: Calculate the percentage of the chord length of the suction surface transition point based on the airfoil chord length and the position parameters of the suction surface transition point.

[0031] In one optional implementation, the position parameter (distance from the airfoil leading edge) of the suction surface transition point at the r / R=0.7 section is obtained from the infrared thermal imaging image as 150mm. According to the formula "Percentage of suction surface transition point chord length = (distance from suction surface transition point to leading edge / airfoil chord length) × 100%", the chord length percentage of the suction surface transition point is calculated to be 10%.

[0032] Step 1133: Calculate the percentage of the chord length of the pressure surface transition point based on the airfoil chord length and the position parameters of the pressure surface transition point.

[0033] In one alternative implementation, the position parameter (distance from the leading edge of the airfoil) of the pressure surface transition point at the r / R=0.7 section is obtained as 225mm, and the chord length percentage of the pressure surface transition point is calculated as 15% by substituting it into the formula.

[0034] Step 1134: Use the chord length percentage of the suction surface transition point and the chord length percentage of the pressure surface transition point as the transition point parameters.

[0035] In one optional implementation, the calculated percentage of the chord length of the suction side transition point (10%) and the percentage of the chord length of the pressure side transition point (15%) are integrated as the transition point parameter for the section with r / R=0.7. Following steps 1131 to 1134 above, the transition point parameters for each section of the blade are calculated to form a complete blade transition point parameter dataset.

[0036] As described above, by characterizing the transition point position by chord length percentage, the influence of different airfoil chord lengths on the transition point parameters is eliminated. The quantified transition point parameters can be directly used as boundary constraints of the aerodynamic simulation model, ensuring the accuracy of the simulation calculation.

[0037] In one embodiment of the present invention, step 120 includes steps 121 to 124.

[0038] Step 121: Obtain the first angle of attack range.

[0039] In one optional implementation, the first angle-of-attack range needs to completely cover the interval where the airfoil lift coefficient reaches its maximum positive and negative angle of attack, ensuring that this range can encompass all possible angle-of-attack conditions during normal operation of the wind turbine blades. For example, the first angle-of-attack range is defined as follows: ∈[ 10°, 20°).

[0040] Step 122: Divide the first angle of attack range into at least two angle of attack calculation nodes according to a uniform angle of attack step size.

[0041] In one optional implementation, the first angle of attack range is divided into angle of attack calculation nodes according to a uniform angle of attack step size. For example, if the angle of attack step size is set to 1°, then the angle of attack calculation nodes include... 10° 9°, ..., 19°, 20°.

[0042] Step 123: Under the boundary constraints, calculate the lift coefficient, drag coefficient, and pitching moment coefficient corresponding to each angle of attack calculation node.

[0043] In one optional implementation, transition point parameters (such as 10% chord length of the suction surface and 15% chord length of the pressure surface) are used as boundary constraints and input into Fluent software. The turbulence model is set to the Transition SST (4 eqn) model, and a UDF file is written and imported into the software, forcibly specifying the transition point location. For each angle-of-attack calculation node, corresponding angle-of-attack conditions are set, and steady-state simulation calculations are performed to obtain the lift coefficient (C1), drag coefficient (Cd), and pitching moment coefficient (Cm) for each node.

[0044] Step 124: Based on the lift coefficient, drag coefficient, and pitching moment coefficient corresponding to each angle of attack calculation node, the blade airfoil aerodynamic coefficients within the first angle of attack range are formed.

[0045] As described above, dividing the calculation nodes by uniform angle of attack step size ensures the continuity and calculation accuracy of aerodynamic coefficients. Using the transition point parameters as boundary constraints eliminates the need to establish an erosion geometry model, significantly reducing the simulation calculation time. At the same time, the core aerodynamic coefficients such as Cl, Cd, and Cm obtained improve the calculation efficiency.

[0046] In one embodiment of the present invention, step 121 includes: based on the normal operating conditions of the wind turbine blades, the lift-to-drag ratio is greatest and the wind turbine operating efficiency is highest when the airfoil angle of attack is around 6°. Therefore, the lift coefficient of the wind turbine blade airfoil is adjusted to reach the range of maximum positive and negative angles of attack. ∈[ [10°, 20°] is the range of the first angle of attack.

[0047] For example, aerodynamic characteristic tests are conducted on the airfoil of wind turbine blades to obtain the lift coefficient (Cl) variation curves at different angles of attack, and the variation law of the curves is observed. Figure 2 The lift coefficient curve of the blade airfoil shown is a function of angle of attack. It is observed that the curve exhibits a clear inflection point at angles of attack of -8° and 12°. At angles of attack of […] Within the range of 8°, 12°, the lift coefficient changes linearly with the angle of attack. The first angle of attack range is set to include [...]. The angle of attack range is [8°, 12°]. [10°, 20°] is used as the first angle of attack range.

[0048] In one embodiment of the present invention, step 130 includes steps 131 to 132.

[0049] Step 131: Input the airfoil aerodynamic coefficients within the first angle of attack range into the extrapolation model to obtain the airfoil aerodynamic coefficients across the entire angle of attack range.

[0050] In one optional implementation, the Viterna extrapolation model is selected, and the input parameters of the extrapolation model are set as the aerodynamic coefficients for the first angle of attack range, while the extrapolation target range is the full angle of attack range. ∈[ [180°, 180°], the angle of attack step size is set to 1°, which is consistent with the angle of attack step size of the first angle of attack range.

[0051] Step 132: Integrate the airfoil aerodynamic coefficients within the first angle of attack range and the airfoil aerodynamic coefficients within the full angle of attack range to obtain the airfoil aerodynamic performance data.

[0052] In one alternative implementation, the aerodynamic coefficients for the first angle of attack range are input into the Viterna model. The model is based on empirical formulas and incorporates the variation patterns of the aerodynamic coefficients to... ∈[ Extrapolate the aerodynamic coefficients within the range of 180°, 180° to obtain the aerodynamic coefficients corresponding to each angle-of-attack node within the full angle-of-attack range.

[0053] As described above, the extrapolation model extended the aerodynamic coefficients from the first angle of attack range to the full angle of attack range, covering all operating conditions of the wind turbine and meeting the requirements of subsequent BEM simulation.

[0054] In one embodiment of the present invention, step 131 includes steps 1311 to 1313.

[0055] Step 1311: Set the extrapolation target range of the extrapolation model to the full angle of attack range.

[0056] In one alternative implementation, the parameter setting interface of the Viterna extrapolation model is opened, and the extrapolation target range is set to the full angle of attack range. [180°, 180°], to ensure that the extrapolation results can cover all possible operating angles of attack of the wind turbine blades, including angles of attack under operating conditions such as start-up, shutdown, pitch control, and extreme wind conditions.

[0057] Step 1312: Set the angle of attack step size of the extrapolation model to be the same as the angle of attack step size of the first angle of attack range.

[0058] In one optional implementation, the angle of attack step size of the first angle of attack range is checked, and the angle of attack step size of the extrapolation model is set to be the same as that of the first angle of attack range (e.g., 1° / step). This ensures that the aerodynamic coefficients of the full angle of attack range obtained by extrapolation are consistent with the aerodynamic coefficients of the first angle of attack range in terms of step size, avoiding data discontinuity caused by step size differences and facilitating subsequent data integration.

[0059] Step 1313: Based on the airfoil aerodynamic coefficients of the blades within the first angle of attack range, extrapolate the calculations using the extrapolation model within the full angle of attack range with the angle of attack step size to obtain the airfoil aerodynamic coefficients of the blades within the full angle of attack range.

[0060] In one alternative implementation, the first angle of attack range (e.g., […]) The aerodynamic coefficients (Cl, Cd, Cm) of 10°, 20° are batch-input into the Viterna extrapolation model. Based on its own empirical formulas and algorithms, the model calculates the aerodynamic coefficients for each angle-of-attack node within the full angle-of-attack range in 1° increments, ultimately outputting the full angle-of-attack range (e.g., [...]). The aerodynamic coefficient dataset for airfoil blades (180°, 180°).

[0061] As described above, by setting the angle-of-attack step size of the extrapolation model to be the same as that of the first angle-of-attack range, the compatibility between the extrapolation data and the basic simulation data is ensured through a unified angle-of-attack step size, avoiding errors in the data integration process. By clearly defining the extrapolation target range as the full angle-of-attack range, it is ensured that the aerodynamic coefficients can cover all operating conditions of the wind turbine.

[0062] In one embodiment of the present invention, step 132 includes steps 1321 to 1322.

[0063] Step 1321: Replace the airfoil aerodynamic coefficient of the corresponding angle of attack interval within the full angle of attack range with the airfoil aerodynamic coefficient of the first angle of attack range.

[0064] In one alternative implementation, based on the first angle of attack range as ∈[ [10°, 20°], this range corresponds to the full angle of attack range ( ∈[ [180°, 180°]) The extrapolated data for the 10°, 20° sub-interval is less accurate than the precise calculated data for the first angle of attack range and needs to be replaced. The full angle of attack range ( ∈[ [180°, 180°]) For all angle-of-attack nodes in the 10°, 20° sub-interval, replace the extrapolated data of the corresponding angle-of-attack node one by one with the accurate calculated data (Cl, Cd, Cm) of the first angle-of-attack range.

[0065] Step 1322: Use the replaced airfoil aerodynamic coefficients for the full angle of attack range as the airfoil aerodynamic performance data.

[0066] In one optional implementation, after the replacement is completed, the aerodynamic coefficient dataset for the entire angle-of-attack range is checked to ensure that the dataset is continuous and reasonable. This replaced aerodynamic coefficient dataset for the entire angle-of-attack range is then combined with the lift-to-drag ratio (Cl / Cd) corresponding to each angle of attack to form blade airfoil aerodynamic performance data for subsequent BEM simulations.

[0067] As described above, replacing the extrapolated values ​​corresponding to the full angle-of-attack range with the accurate simulated values ​​of the first angle-of-attack range significantly improves the accuracy of the aerodynamic coefficients in the overlapping region, avoiding the impact of extrapolation errors on subsequent simulation results. The integrated aerodynamic performance data for the full angle-of-attack range is continuous and complete, and can be directly used for the simulation of the wind turbine's overall performance, simplifying the subsequent data processing flow, improving work efficiency, and ensuring the accuracy of the overall performance evaluation.

[0068] In one embodiment of the present invention, steps 140 to 150 are included after step 130.

[0069] Step 140: Using the blade element momentum theory, calculate the overall power curve of the eroded wind turbine blade based on the aerodynamic performance data of the blade airfoil.

[0070] In one optional implementation, the aerodynamic performance data of the blade airfoil obtained in step 1132 is input into the BEM simulation system, the wind turbine parameters (such as blade radius, speed range, pitch angle, etc.) are set, and the blade is divided into multiple blade elements using the blade element momentum theory. The aerodynamic force of each blade element is calculated one by one, and then the power curve of the whole machine after erosion is obtained, that is, the output power of the wind turbine at different wind speeds.

[0071] Step 150: Based on the overall power curve and the preset wind speed distribution of the wind farm, the annual power generation loss of the wind turbine blades is obtained.

[0072] In one optional implementation, historical wind speed data of the wind turbines is collected, and the wind speed distribution curve of the wind field (such as the Weibull distribution) is statistically obtained to determine the frequency of occurrence of different wind speeds in the wind field. Based on the overall power curve of the turbine after erosion, combined with the wind speed distribution of the wind field, the annual power generation of the wind turbine after erosion is calculated. Simultaneously, the annual power generation data of the wind turbine under clean conditions is retrieved, and the result is calculated using the formula: "Annual power generation loss = (Annual power generation under clean conditions)". The annual power generation loss is calculated as "(annual power generation after erosion) / annual power generation in clean state × 100%".

[0073] As described above, by using the aerodynamic performance data of the blade airfoil to calculate the overall power curve and annual power generation loss of the eroded wind turbine blades, the local airfoil performance is correlated with the overall performance. By combining the wind speed distribution of the wind farm, the calculation of annual power generation loss is more in line with the actual situation on site, and the results are more valuable for reference. The entire calculation process is fast and efficient, and can provide operation and maintenance personnel with an accurate assessment of power loss, assist in the formulation of reasonable maintenance strategies, and reduce operation and maintenance costs.

[0074] Figure 3 This is another flowchart illustrating a method for calculating the aerodynamic performance of wind turbine blades according to an embodiment of the present disclosure. Please refer to... Figure 3 The following is an application embodiment of the present invention, taking the assessment of annual power generation loss due to erosion of wind turbine blades in a 2.5MW wind farm as a specific application scenario, and the specific implementation includes steps 201 to 205.

[0075] Step 201: Obtain temperature maps of the pressure and suction surfaces of the wind turbine blades using infrared imaging. In one optional implementation, a high-definition infrared thermal imager is used. With the wind turbines in the 2.5MW wind farm shut down, comprehensive images are taken of all cross-sections along the span of the turbine blades. The focus is on acquiring surface temperature distribution images of the suction and pressure surfaces. During the imaging process, it is ensured that the lens is unobstructed and the images are clear, accurately capturing temperature changes in the boundary layer transition region of the blade surface. This provides high-quality image data for subsequent transition point identification, for example... Figure 4 The diagram showing the transition zone of the wind turbine blades and Figure 5 The diagram shown illustrates the detection of the laminar and turbulent flow interface based on the acoustic intensity variation under airfoil surface pressure fluctuations.

[0076] Step 202: Determine the location of the airfoil laminar and turbulent interface at the erosion site.

[0077] In one optional implementation, an image processing algorithm (such as a threshold segmentation algorithm) is used to analyze the temperature distribution image acquired in step 201. Based on the temperature jump characteristics caused by the difference in heat exchange intensity between the turbulent and laminar regions during the boundary layer transition, the laminar and turbulent interface points (i.e., transition points) of each airfoil section of the blade are automatically identified. Taking the blade section with r / R=0.7 as an example, the interface point between laminar and turbulent flow on the suction surface is identified as 10% chord length, and the interface point between laminar and turbulent flow on the pressure surface is identified as 15% chord length. Compared with the transition points of 45% chord length (percentage of suction surface chord length) and 60% chord length (percentage of pressure surface chord length) of this section under clean conditions, it can be clearly determined that there is significant erosion at this section, and the transition point has obviously shifted forward. At the same time, the transition point positions of other sections along the span of the blade are recorded, thus completing the determination of the airfoil transition points at all erosion locations.

[0078] Step 203: Calculate the aerodynamic performance of the eroded airfoil using simulation software.

[0079] In an optional implementation, the transition point parameters of each airfoil section determined in step 202 (e.g., for a section with r / R=0.7, the suction surface chord length percentage is 10%, and the pressure surface chord length percentage is 15%) are input into the calculation system of this invention. The system automatically reads the geometric coordinates of the airfoil corresponding to the wind turbine blade (obtained by interpolation of the airfoil at two positions before and after the blade design data), and simultaneously automatically reads the actual operating conditions of the wind turbine in the wind farm. Subsequently, the system calls CFD simulation software (such as Fluent software), uses the transition point parameters as boundary constraints, specifies the transition point position by writing a UDF file, calculates the lift coefficient Cl and drag coefficient Cd within the angle of attack range [-10°, 20°], and obtains the aerodynamic coefficient of the eroded airfoil within this angle of attack range.

[0080] Step 204: Obtain airfoil aerodynamic performance data for the entire angle of attack range through extrapolation model.

[0081] In one optional implementation, the system calls the Viterna extrapolation model, inputting the airfoil aerodynamic coefficients (C1, Cd) within the angle-of-attack range [-10°, 20°] calculated in step 203 into the model. The extrapolation target range is set to the full angle-of-attack range [-180°, 180°], and the angle-of-attack step size is set to be consistent with the angle-of-attack step size in the CFD simulation in step 203. The airfoil aerodynamic coefficients within the full angle-of-attack range are calculated using the extrapolation model. Subsequently, the accurate simulation coefficients from step 203 are integrated with the extrapolated full angle-of-attack coefficients, and the extrapolated coefficients for the corresponding angle-of-attack intervals are replaced with the accurate simulation coefficients. Duplicate data is removed, and missing data is filled in, finally obtaining airfoil aerodynamic performance data covering the full angle-of-attack range, and generating a standardized airfoil aerodynamic performance file. For example, the airfoil aerodynamic coefficients of a clean, undamaged airfoil are compared with those of a leading-edge eroded airfoil. Figure 6The diagram showing the airfoil aerodynamic coefficient curves compares the values ​​of the horizontal axis (full angle of attack) and the vertical axis (ratio of lift coefficient Cl to drag coefficient Cd).

[0082] Step 205: Input the data into the blade element momentum theory model to obtain the actual power curve of the wind turbine and the annual power generation loss.

[0083] In one optional implementation, the airfoil aerodynamic performance file generated in step 204 is input into a blade element momentum theory (BEM) simulation system. The system divides the blade into several blade elements along its spanwise direction, calculates local aerodynamic forces based on the aerodynamic performance data of each blade element, and obtains the power value of the eroded blade at different wind speeds through momentum theorem integration, thus plotting the actual overall power curve of the wind turbine. Simultaneously, wind speed distribution data (characterized using Weibull distribution) of the 2.5MW wind farm is acquired, and the annual occurrence hours of different wind speeds are counted. Combined with the overall power curve of the eroded blade, the annual power generation under erosion conditions is calculated and compared with the annual power generation of clean blades to obtain the annual power generation loss. For example, in this embodiment, compared to the clean state, the annual power generation decreases by approximately 3.7%. The operation and maintenance decision system, combining this annual power generation loss with blade maintenance costs, automatically provides reasonable maintenance suggestions, offering direct reference for wind farm operation and maintenance. For example, the power curve of a clean, undamaged blade is compared with the power curve of a blade with leading-edge erosion. Figure 7 The power curve comparison chart shown has wind speed on the horizontal axis and the power output of the fan on the vertical axis. This refers to the minimum wind speed at which the wind turbine begins to generate electricity; This refers to the wind speed at which the fan stops for protection due to excessive wind speed.

[0084] Please refer to Figure 8 The present invention also provides a wind turbine blade aerodynamic performance calculation terminal 800, including a memory 801, a processor 802, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the various steps of the wind turbine blade aerodynamic performance calculation method described above.

[0085] This invention simplifies the characterization of leading-edge erosion of wind turbine blades by using transition point parameters, eliminating the need to model complex erosion geometries and transforming multi-morphological, irregular erosion problems into a single measurable parameter, significantly reducing computational complexity. Infrared thermal imaging technology is used to capture the location of the transition point, and the transition point parameter is quantified by chord length percentage, reducing the difficulty of parameter acquisition and improving data universality and accuracy. By selecting an appropriate angle of attack range based on the wind turbine's operating conditions and dividing the calculation nodes with uniform step sizes, aerodynamic simulation is performed under the boundary constraints of the transition point parameter, balancing the accuracy and efficiency of aerodynamic coefficient calculation. An extrapolation model is used to extend the aerodynamic coefficients from a small range of angles of attack to the full angle of attack range, and data integration and replacement improve the accuracy of overlapping intervals, ensuring that aerodynamic performance data covers all wind turbine operating conditions and meets subsequent simulation requirements. By combining blade element momentum theory with wind speed distribution in the wind farm, a complete calculation from airfoil aerodynamic performance to the overall power curve and annual power generation loss is achieved, closely matching actual field needs and providing accurate support for wind farm operation and maintenance decisions. This application solves the problems of complex calculations, long cycles, disconnect from on-site testing, and poor universality, and achieves rapid, efficient, and accurate calculation of the aerodynamic performance of wind turbine blades.

[0086] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for calculating the aerodynamic performance of a wind turbine blade, characterized in that, include: Obtain the parameters of the turning point on the wind turbine blades; The transition point parameters are input as boundary constraints into the aerodynamic simulation model to calculate the airfoil aerodynamic coefficients within the first angle of attack range. Based on the aerodynamic coefficients of the airfoil within the first angle of attack range, the aerodynamic performance data of the airfoil are obtained through an extrapolation model.

2. The method according to claim 1, characterized in that, The acquisition of the turning point parameters on the wind turbine blades includes: Infrared thermal imaging technology was used to acquire images of the surface temperature distribution of the wind turbine blades. Based on the temperature jump characteristics of the transition region of the wind turbine blade, the suction surface transition point and pressure surface transition point of the blade airfoil are identified from the surface temperature distribution image. The transition point parameters are obtained based on the transition point of the suction surface and the transition point of the pressure surface.

3. The method according to claim 2, characterized in that, The step of obtaining the transition point parameters based on the suction surface transition point and the pressure surface transition point includes: Collect the airfoil chord length of the wind turbine blades; Calculate the percentage of the chord length at the suction surface transition point based on the airfoil chord length and the position parameters of the suction surface transition point; Calculate the percentage of the chord length of the pressure surface transition point based on the airfoil chord length and the position parameters of the pressure surface transition point; The percentage of the chord length at the suction surface transition point and the percentage of the chord length at the pressure surface transition point are used as the transition point parameters.

4. The method according to claim 1, characterized in that, The step of inputting the transition point parameters as boundary constraints into the aerodynamic simulation model to calculate the airfoil aerodynamic coefficients within the first angle of attack range includes: Obtain the first angle of attack range; Divide the first angle of attack range into at least two angle of attack calculation nodes according to a uniform angle of attack step size; Under the boundary constraints, calculate the lift coefficient, drag coefficient, and pitching moment coefficient corresponding to each angle of attack calculation node; The airfoil aerodynamic coefficients within the first angle of attack range are formed based on the lift coefficient, drag coefficient, and pitching moment coefficient corresponding to each angle of attack calculation node.

5. The method according to claim 4, characterized in that, The acquisition of the first angle of attack range includes: Based on the normal operating conditions of the wind turbine blades, the range in which the lift coefficient of the blade airfoil reaches the maximum positive and negative angle of attack is defined as the first angle of attack range.

6. The method according to claim 1, characterized in that, The step of obtaining the blade airfoil aerodynamic performance data through an extrapolation model based on the blade airfoil aerodynamic coefficient within the first angle of attack range includes: The aerodynamic coefficients of the airfoil within the first angle of attack range are input into the extrapolation model to obtain the aerodynamic coefficients of the airfoil across the entire angle of attack range. The blade airfoil aerodynamic performance data are obtained by integrating the airfoil aerodynamic coefficients within the first angle of attack range and the airfoil aerodynamic coefficients within the full angle of attack range.

7. The method according to claim 6, characterized in that, The step of inputting the airfoil aerodynamic coefficients within the first angle of attack range into the extrapolation model to obtain the airfoil aerodynamic coefficients across the entire angle of attack range includes: Set the extrapolation target range of the extrapolation model to the full angle of attack range; Set the angle of attack step size of the extrapolation model to be the same as the angle of attack step size of the first angle of attack range; Based on the airfoil aerodynamic coefficients within the first angle of attack range, the airfoil aerodynamic coefficients within the full angle of attack range are obtained by extrapolation calculation using the extrapolation model with the angle of attack step size.

8. The method according to claim 6, characterized in that, The process of integrating the airfoil aerodynamic coefficients within the first angle of attack range and the airfoil aerodynamic coefficients across the entire angle of attack range to obtain the airfoil aerodynamic performance data includes: The airfoil aerodynamic coefficient within the first angle of attack range is used to replace the airfoil aerodynamic coefficient within the corresponding angle of attack range across the entire angle of attack range; The aerodynamic coefficients of the blade airfoil across the entire angle of attack range after the replacement are used as the aerodynamic performance data of the blade airfoil.

9. The method according to claim 1, characterized in that, The step of obtaining airfoil aerodynamic performance data through extrapolation model based on the airfoil aerodynamic coefficients within the first angle of attack range, followed by: Using the blade element momentum theory, the overall power curve of the eroded wind turbine blade is calculated based on the aerodynamic performance data of the blade airfoil. Based on the overall power curve and the preset wind speed distribution of the wind farm, the annual power generation loss of the wind turbine blades is obtained.

10. A terminal for calculating the aerodynamic performance of a wind turbine blade, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the aerodynamic performance calculation method for wind turbine blades as described in any one of claims 1 to 9.

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