CFD-based wind turbine generator load simulation method under high slope

Abstract

A CFD (computational fluid dynamics)-based wind turbine generator load simulation method under a high slope comprises the following steps: step 1, acquiring topographic data and position information of the high slope: acquiring the topographic data and position information of the high slope through a multi-source data acquisition means; step 2, constructing a high slope simplified physical model according to the high slope topographic data and the machine position information; 3, a CFD tool is used for flow field numerical simulation calculation, and according to the constructed high slope simplified physical model, the CFD tool is used for obtaining the wind speed distribution and turbulence intensity distribution conditions of the whole wind wheel face of the wind turbine generator; step 4, generating a target wind seed file by using a TurbSim tool; 5, establishing a high slope wind file library; step 6, calculating the dynamic response of the whole machine; and obtaining an accurate load result of the wind turbine generator under the high slope terrain. The accuracy of the simulation result is improved, and the safety, the power generation efficiency and the service life of the wind turbine generator are improved.

Description

Technical Field

[0001] The invention belongs to the technical field of wind turbine load simulation, and in particular relates to a CFD-based wind turbine load simulation method under a high slope. Background Art

[0002] With the continuous development of wind power generation technology, wind farm site selection and wind turbine design are facing more and more complex terrain conditions. Especially in high-slope terrain, due to the complexity and variability of the terrain, the working environment of wind turbines has become more demanding. In order to ensure that wind turbines can operate safely and efficiently under these conditions, it is necessary to accurately simulate the loads of wind turbines in high-slope terrain. Traditional simulation methods often find it difficult to accurately capture the impact of high-slope terrain on wind farm flow characteristics, so methods based on computational fluid dynamics (CFD) have gradually become a research hotspot.

[0003] Traditional simulation methods often use simplified physical models to simulate terrain, ignoring terrain details, resulting in inaccurate simulation results. Secondly, in order to reduce computing resource consumption, the grid division in traditional methods is often coarse and cannot capture terrain details and small-scale turbulence. In addition, many existing methods lack comparative verification with actual measurement data, resulting in low credibility of simulation results. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a CFD-based method for simulating the load of wind turbines under high slopes. By acquiring high-precision terrain and machine position information, building a detailed physical model, and combining advanced CFD technology with tools such as TurbSim and Bladed, the working environment of wind turbines under complex terrain can be simulated more accurately. The present invention not only improves the accuracy of the simulation results, but also provides a scientific basis for the design optimization of wind turbines and the site selection of wind farms, which helps to improve the safety, power generation efficiency and service life of wind turbines.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is: A CFD-based method for simulating wind turbine loads on high slopes, comprising the following steps: Step 1: Obtain high slope terrain data and camera position information: obtain high slope terrain data and camera position information through multi-source data collection; Step 2: Construct a simplified physical model of the high slope based on the high slope terrain data and camera position information; Step 3: Use CFD tools to perform numerical simulation calculations of the flow field: Based on the constructed simplified physical model of the high slope, use CFD tools to obtain the wind speed distribution and turbulence intensity distribution on the entire rotor surface of the wind turbine; Step 4: Generate the target wind seed file using the TurbSim tool; Step 5, establish a high slope wind file library; Step 6: Calculate the dynamic response of the whole machine; obtain the accurate load result of the wind turbine under the high slope terrain.

[0006] Preferably, the sub-steps of step 1 are: Step 1.1, multi-source data acquisition: use satellite image acquisition equipment to obtain satellite terrain image data, which contains two-dimensional image information of terrain and corresponding coordinate information; process the satellite terrain image data through remote sensing image processing tools to generate a digital elevation model; Use drone equipment to take aerial photos and obtain drone terrain image data and altitude data; Use total station equipment, GPS equipment and ground measurement equipment to conduct field measurements of high slope terrain to obtain high-precision terrain data points, which contain the coordinate information of the geographical location and elevation information; Step 1.2, data fusion: compare the elevation data in the digital elevation model with the ground measurement data obtained by the ground measurement equipment point by point; identify and remove the outliers that obviously deviate from most data points; obtain terrain data with higher accuracy and reliability, and provide more accurate basic data for the subsequent construction of a simplified physical model of a high slope. The basic data includes terrain elevation information, two-dimensional image information, and coordinate information; Step 1.3: Automated data processing: Use Python modules to automatically read satellite terrain image data, drone terrain image data and altitude data, and ground measurement data; convert data from different sources into a unified data format; at the same time, perform coordinate system unification operations to ensure that the coordinate systems of all data are consistent; finally, integrate the processed data into a database; Step 1.4, perform data verification: re-measure the high slope terrain at different time points and verify the aircraft position information on site; compare the data changes before and after, and update the terrain data in a timely manner; ensure the timeliness and accuracy of the data, and obtain accurate high slope terrain data and aircraft position information.

[0007] Preferably, the sub-steps of step 2 are as follows: Step 2.1, determining the scope and scale of the simplified physical model of the high slope: obtaining high slope terrain data and camera position information, wherein the high slope terrain data includes terrain elevation information, two-dimensional image information and coordinate information; analyzing the terrain and camera position information to determine the scope of the terrain area to be simulated; determining the scope and scale of the simplified physical model of the high slope; Step 2.2, generate digital elevation model: using the elevation information in the acquired terrain data, integrating data from different sources, and using geographic information system tools to generate a digital elevation model to reflect the ups and downs of the terrain; The data from different sources include: digital elevation models generated from satellite terrain image data, elevation information generated with the assistance of drone altitude data, and elevation information from ground measurement data; Step 2.3, simplifying terrain features: extracting key terrain features from the digital elevation model, wherein the key terrain features include obtaining slope information by calculating the elevation change rate in the digital elevation model; obtaining curvature information by calculating the curvature of the terrain surface; appropriately simplifying the terrain features according to the actual needs of the wind turbine; Step 2.4: Use the adaptive meshing function in the CFD tool to automatically increase the mesh density to capture details in areas with large terrain changes, steep slopes, and complex curvatures; reduce the mesh density to reduce computing resource consumption in areas with relatively flat terrain and small changes; and finally divide the mesh to adapt to the complexity of the terrain; The CFD tools include ANSYS Fluent and OpenFOAM; Step 2.5, multi-scale modeling: First, build a macroscopic high slope terrain model, and use the digital elevation model and terrain feature information to build the general outline and trend of the overall terrain; determine the overall terrain trend and wind direction distribution, and analyze it in combination with meteorological data and terrain features; conduct micro-modeling in local areas, refine the details of terrain features and wind turbines, and finally establish a multi-scale physical model; Step 2.6, perform model verification: simulate the wind speed distribution under standard wind field conditions, compare it with the theoretical value, and check whether the model can accurately simulate the basic characteristics of the wind field; the theoretical value is calculated by the wind field theory formula; finally, it is used to verify the basic function and accuracy of the model and obtain a simplified physical model of the high slope. Preferably, the sub-steps of step 3 are: Step 3.1, select CFD tools: determine the specific tools used for flow field numerical simulation calculations, including ANSYS Fluent and OpenFOAM; Step 3.2, meshing: Based on the constructed simplified physical model of the high slope, meshing is performed in the selected CFD tool; specific meshes suitable for flow field calculation are divided, and the specific meshes include mesh density and mesh type in different regions; Step 3.3, setting boundary conditions: including the following: setting the wind speed distribution and turbulence intensity at the inlet boundary; Set the pressure and turbulence conditions at the outlet boundary; Set the wall function and roughness parameters of the ground boundary; Set the rotation boundary conditions and damping zones at the wind turbine boundary; Step 3.4, select the physical model: Consider the wind field characteristics under the high slope terrain and the turbulent characteristics of the wind, and select a suitable physical model; the wind field characteristics include the blocking and acceleration effects of the terrain on the wind; Step 3.5, set up parallel computing: Use the MPI parallel computing framework tool to decompose the CFD computing task into multiple subtasks; determine the subtask division method based on the computing resources and the characteristics of the flow field calculation; assign the decomposed subtasks to different computing nodes for parallel computing; use the communication mechanism of the MPI framework to achieve data exchange and synchronization between computing nodes to ensure the correctness and efficiency of the calculation; Step 3.6: Verify the results: Compare the actual measurement data with the simulation results to verify the accuracy of the simulation results.

[0008] Preferably, the sub-steps of step 4 are: step 4.1, using CFD tools to simulate wind speed distribution and turbulence intensity distribution data; obtaining parameter characteristics of the actual wind field, the parameter characteristics including average wind speed, wind speed standard deviation, turbulence intensity range, and wind direction distribution law; Step 4.2, perform parameter optimization: optimize the input parameters of TurbSim through the wind speed, wind direction, and turbulence intensity data obtained through field measurements in high slope areas, as well as the results obtained from the statistical analysis in step 4.1; adjust the turbulence model parameters, which include turbulence intensity and turbulence scale; at the same time, adjust the random number seed to generate different random wind field sequences; determine the optimal input parameter combination through multiple tests and comparisons; Step 4.3, generate a single sample wind seed file: Use the TurbSim tool to set the optimized input parameters determined in step 4.2 into the TurbSim tool; during the setting process, carefully check the value of each parameter to ensure accuracy; then run the TurbSim tool to generate a wind field time series file, i.e., a wind seed file, based on the input parameters; the wind seed file contains wind speed and wind direction information over a period of time, simulating the changes in the actual wind field; Step 4.4, multi-condition simulation: determine a series of different wind speed value ranges, the wind speed value ranges include low wind speed, medium wind speed and high wind speed; For wind direction, different dominant wind directions are considered, including easterly, westerly, southerly and northerly; For turbulence intensity, different intensity levels are determined, including low turbulence intensity, medium turbulence intensity and high turbulence intensity; then, the input parameters are adjusted multiple times, that is, the input parameters of TurbSim are adjusted according to different combinations of wind speed, wind direction and turbulence intensity; Step 4.5: Use Python programming tools to generate a large number of wind seed files for different working conditions, and name and classify the files for storage, making it easier to find and use the files later.

[0009] Preferably, the sub-steps of step 5 are: Step 5.1: Develop standardized naming rules; Step 5.2, classify the wind seed files according to factors including wind speed range, turbulence intensity range, and terrain characteristics; Step 5.3, name each wind seed file according to the standardized naming rules; Step 5.4, store the wind seed files of different categories into corresponding folders, and ensure that the file storage path is clear and easy to manage; Step 5.5: Establish a database management system.

[0010] Preferably, the sub-steps of step 6 are: step 6.1, determining the analysis conditions: selecting different wind seed files from the wind file library to determine the conditions to be analyzed; each condition corresponds to a set of specific wind seed files; Step 6.2, conduct multi-condition analysis: Use the Bladed tool to import wind seed files under different working conditions in turn; during the import process, ensure that the file path is correct and the parameter settings are accurate; then, simulate the operation of the wind turbine under different wind field conditions; through the simulation function of the Bladed tool, consider the structural characteristics of the wind turbine and the blade rotation factors, simulate the dynamic response of the wind turbine under different wind speeds, wind directions and turbulence intensities; analyze the load changes of the wind turbine under different working conditions; obtain the performance data of the wind turbine under various working conditions, including the load size and change law under different working conditions; Step 6.3, select the advanced dynamics model: analyze the nonlinear phenomena that may occur during the operation of the wind turbine, including large deformation of the blades and vibration of the tower; at the same time, consider the flexibility of the wind turbine structure, that is, the structure will deform under the action of force; finally determine a more complex advanced dynamics model; Step 6.4, perform dynamic calculation: use the selected advanced dynamic model and Bladed tool; use the data in the wind file library as input, and perform calculation in combination with the advanced dynamic model; obtain preliminary dynamic response results, which include the displacement, velocity, acceleration, and load information of the wind turbine under different wind field conditions; Step 6.5, result verification: obtain actual operating data through sensors installed on the wind turbine, including wind speed, wind direction, and load information; compare these actual data with the simulation results and analyze the differences between the two; if there is a large deviation, further adjust the model parameters and calculation settings; verify the accuracy of the simulation results, and obtain the dynamic response of the wind turbine under high slope terrain; obtain accurate load results of the wind turbine under high slope terrain.

[0011] Preferably, in step 3.2, the criterion for meshing is: (1) The complexity of the high-slope terrain is evaluated. Areas with dramatic terrain changes, steep slopes, and complex curvatures are considered to be areas of high complexity. For areas of high complexity, a finer grid density is used. The finer grid density refers to setting the grid size to a smaller value to more accurately capture terrain details and flow field changes. (2) For areas with relatively flat terrain and less variation, a coarser grid density is used to reduce the consumption of computing resources; (3) Select an appropriate grid type based on the computational accuracy requirements. Grid types include structured grids and unstructured grids. If you need to accurately simulate a regular-shaped area, select a structured grid. If you need to simulate complex terrain, select an unstructured grid.

[0012] Preferably, in step 3.6, the actual measurement data is compared with the simulation results to verify the accuracy of the simulation results, including: (1) Set up multiple wind speed measurement points on the high slope terrain, use wind speed measuring instruments to conduct actual measurements, and obtain wind speed and turbulence intensity data at different locations; the locations of the measurement points should cover different areas of the high slope, including key locations such as areas with complex terrain and near wind turbines; (2) Compare the actual measured data with the simulation results; the comparison indicators include wind speed, wind speed distribution, and turbulence intensity; perform comparative analysis by drawing charts and calculating errors; (3) If there is a large deviation, analyze the cause of the deviation, which may include unreasonable model parameter settings, inaccurate boundary conditions, and inappropriate mesh division; Then adjust the model parameters and calculation settings, including adjusting the parameters of the physical model, optimizing the mesh density and type, modifying the boundary conditions, and finally re-simulating the calculation; (4) The accuracy of the simulation results was verified, and the specific wind speed distribution and turbulence intensity distribution on the entire wind turbine rotor surface were obtained. The specific wind speed distribution and turbulence intensity distribution included wind speed values, turbulence intensity values ​​and distribution patterns at different locations.

[0013] A CFD-based high slope wind turbine load simulation system adopts the CFD-based high slope wind turbine load simulation method; comprising: Acquisition unit: used to obtain high slope terrain data and camera position information: high slope terrain data and camera position information are obtained through multi-source data acquisition methods; Modeling unit: used to construct a simplified physical model of the high slope based on the high slope terrain data and aircraft position information; Simulation unit: including CFD tools, using CFD tools to perform numerical simulation calculations of flow fields: based on the constructed simplified physical model of high slopes, using CFD tools to obtain the wind speed distribution and turbulence intensity distribution on the entire rotor surface of the wind turbine; Storage unit: Generate target wind seed files using TurbSim tool; Establish high slope wind file library; Result input unit: used to calculate the dynamic response of the whole machine; to obtain accurate load results of wind turbines under high slope terrain.

[0014] The present invention can achieve the following beneficial effects: 1. The present invention ensures the high accuracy of all input data, especially in areas with complex terrain. It improves data accuracy through multi-source data fusion, regular field verification and other measures, which directly affects the accuracy of simulation results. Specifically, multi-source data fusion includes combining satellite remote sensing data, drone measurement data, ground measurement data, etc., and improving the accuracy of terrain data through data processing and fusion algorithms. Regular field verification includes re-measuring high slope terrain at different time points, comparing the changes in data before and after, and updating terrain data in a timely manner to ensure the timeliness and accuracy of the data.

[0015] 2. Use high-performance computing resources and parallel computing technology, such as using advanced turbulence models, parallel computing and other methods to improve computing efficiency and shorten simulation time. Specifically, the use of advanced turbulence models can more accurately simulate the turbulence characteristics of the wind field and improve the accuracy of the simulation, but the computing cost is high. Through parallel computing technology, the computing tasks are distributed to multiple computing nodes for simultaneous calculation, which can greatly shorten the computing time. For example, using the MPI parallel computing framework, the CFD computing task is decomposed into multiple subtasks and distributed to different computing nodes for parallel computing.

[0016] 3. Verify the accuracy and reliability of the simulation results through actual measurement data and multi-condition analysis. Compare with the actual operation data, adjust the model parameters and calculation settings, and ensure that the simulation results are consistent with the actual situation. Specifically, by setting wind speed measurement points on high slope terrain, actual measurements are taken to obtain wind speed and turbulence intensity data, and then the actual measurement data is compared with the simulation results. If there is a large deviation, analyze the cause of the deviation, adjust the model parameters and calculation settings, and re-simulate the calculation until the simulation results are consistent with the actual measurement data. At the same time, through multi-condition analysis, simulate the operation of wind turbines under different wind field conditions, evaluate the performance of wind turbines under various conditions, and further verify the accuracy and reliability of the simulation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0018] The preferred solution is Figure 1 As shown in the figure, a CFD-based wind turbine load simulation method under high slopes is shown. The specific scheme is as follows: 1. Obtain high slope terrain characteristics and camera position information: Step 1: Multi-source data collection: Use satellite image acquisition equipment to obtain high-resolution satellite terrain image data, which contains two-dimensional image information of the terrain and corresponding coordinate information. Use professional remote sensing image processing tools to process these data to generate a digital elevation model (DEM). The specific process may include operations such as image registration, geometric correction, and stereo pair matching to extract the elevation information of the terrain and obtain a digital elevation model.

[0019] Use drone equipment for aerial photography to obtain drone terrain image data and altitude data, etc. Drone terrain image data can provide detailed image information of high slope terrain, and altitude data can assist in determining the elevation changes of terrain.

[0020] Use total station equipment, GPS equipment and other ground surveying equipment to conduct field surveys of high slope terrain and obtain high-precision terrain data points, which contain coordinate information of geographic location and elevation information, etc. Surveyors will set up measurement points at different locations on the high slope and conduct multiple measurements to improve the accuracy of the data.

[0021] Step 2: Data Fusion: The elevation data in the digital elevation model (DEM) generated in the first step are compared point by point with the ground measurement data obtained by the ground measurement equipment.

[0022] Identify and remove outliers that are significantly different from most data points. For example, if the elevation value of a data point is very different from the surrounding data points and does not match the ground measurement data, it can be judged as an outlier and removed. You can set a certain threshold range to judge outliers, such as when the difference between the elevation value and the surrounding data points exceeds a certain set value, it is considered an outlier.

[0023] If there are missing data in some areas in the digital elevation model (DEM) or ground measurement data, the missing values ​​can be filled by interpolation using the information of surrounding data points. For example, interpolation methods such as Kriging interpolation and inverse distance weighted interpolation can be used to estimate the elevation values ​​of the missing areas based on the elevation information of surrounding known data points.

[0024] Results: The terrain data with higher accuracy and reliability were obtained, which provided more accurate basic data for the subsequent steps of building simplified physical models of high slopes. The basic data included terrain elevation information, two-dimensional image information, coordinate information, etc.

[0025] Step 3: Automated data processing: The Python module is used to automatically read the satellite terrain image data, drone terrain image data and altitude data, and ground measurement data obtained in the first step.

[0026] Perform data format conversion to convert data from different sources into a unified data format for subsequent processing. At the same time, perform coordinate system unification operations to ensure that the coordinate system of all data is consistent.

[0027] Integrate the processed data into a database.

[0028] Result: Improve data processing efficiency, reduce errors, and obtain an integrated database.

[0029] Step 4: Data Verification The high slope terrain was re-measured at different time points, using the same measurement equipment and methods as in the first step.

[0030] Compare the data changes before and after and update the terrain data in time.

[0031] Conduct on-site verification of aircraft seat information.

[0032] Result: Ensure data timeliness and accuracy, and obtain accurate high slope terrain data and aircraft position information.

[0033] 2. Construct a simplified physical model of high slope: Step 1: Determine the scope and scale of the simplified physical model of the high slope; Input: The high slope terrain data and camera position information obtained in the first step, where the high slope terrain data includes terrain elevation information, two-dimensional image information, coordinate information, etc. Analyze the terrain and camera position information to determine the range of the terrain area to be simulated. According to the actual situation and computing resources, select the appropriate scale of the simplified physical model of the high slope. Finally, the scope and scale of the simplified physical model of the high slope are determined.

[0034] Step 2: Generate digital elevation model: Using the elevation information in the terrain data obtained in the first step, integrate data from different sources, such as the digital elevation model generated by satellite terrain image data, the elevation information generated with the assistance of drone altitude data, and the elevation information in ground measurement data. Use professional geographic information system tools (such as ArcGIS, QGIS, etc.) to generate a digital elevation model (DEM) to reflect the ups and downs of the terrain.

[0035] Result: A digital elevation model is obtained.

[0036] Step 3: Simplify terrain features Extract key terrain features from the digital elevation model generated in the second step, such as obtaining slope information by calculating the rate of elevation change in the digital elevation model, and obtaining curvature information by calculating the curvature of the terrain surface.

[0037] The terrain features are appropriately simplified according to the actual needs of wind turbines.

[0038] Result: Simplified terrain features.

[0039] Step 4: Perform adaptive meshing: Use adaptive meshing capabilities in CFD tools such as ANSYS Fluent, OpenFOAM, etc.

[0040] For areas with large terrain changes, steep slopes, and complex curvature, the mesh density is automatically increased to capture the details.

[0041] For areas with flatter terrain and less variation, reduce the mesh density to reduce computing resource consumption.

[0042] Result: A grid is created that adapts to the complexity of the terrain.

[0043] Step 5: Multi-scale modeling: First, a macroscopic high slope terrain model is constructed, and the general outline and trend of the overall terrain are constructed using the digital elevation model and terrain feature information.

[0044] To determine the overall terrain trend and wind direction distribution, meteorological data and terrain characteristics can be combined for analysis.

[0045] Micro-modeling is performed in local areas to refine the terrain features and details of wind turbines, such as a more detailed depiction of the terrain around wind turbines.

[0046] Results: A multi-scale physical model was established.

[0047] Step 6: Model verification: To simulate the wind speed distribution under standard wind field conditions, common wind field models can be used for simulation.

[0048] Compare with the theoretical value to check whether the model can accurately simulate the basic characteristics of the wind field. The theoretical value can be calculated using the wind field theory formula.

[0049] If there is actual measurement data, compare it with the actual measurement data.

[0050] Results: The basic functions and accuracy of the model were verified, and a simplified physical model of the high slope was obtained.

[0051] 3. Use CFD tools to perform numerical simulation of flow field: Step 1: Select CFD tool: Input: Simplified physical model of the high slope constructed in step 2.

[0052] Choose from common CFD tools based on the specific needs of the project, such as the accuracy requirements for wind field simulation, the ability to handle complex terrain, and the actual situation of computing resources, including the computer's hardware configuration (number of CPU cores, memory size, etc.) and available computing time. For example, if the project has high accuracy requirements and sufficient computing resources, you can choose ANSYS Fluent, which has powerful functions and a wide range of application cases; if you pursue open source and flexibility, you can choose OpenFOAM.

[0053] Results: Specific tools for numerical simulation of flow fields were identified, such as ANSYS Fluent or OpenFOAM.

[0054] Step 2: Meshing Based on the simplified physical model of the high slope constructed in the second step, meshing operations are performed in the selected CFD tool. First, the complexity of the high slope terrain is evaluated. Areas with drastic terrain changes, steep slopes, and complex curvatures are considered to be areas of high complexity. For areas with high complexity, a finer mesh density is used, for example, the mesh size can be set to a smaller value to more accurately capture terrain details and flow field changes. For areas with flatter terrain and less changes, a coarser mesh density is used to reduce the consumption of computing resources. At the same time, the appropriate mesh type is selected according to the calculation accuracy requirements. Common ones are structured meshes and unstructured meshes. If you need to accurately simulate areas with regular shapes, you can choose a structured mesh; for complex terrain, unstructured meshes are more advantageous and can better adapt to irregular geometric shapes.

[0055] Result: The specific grid suitable for flow field calculation is divided, including the grid density and grid type in different areas.

[0056] Step 3: Set boundary conditions: Set the wind speed distribution and turbulence intensity at the inlet boundary. By consulting relevant meteorological data or conducting field measurements, obtain the typical wind speed distribution in high slope areas. For example, the average wind speed and the law of wind speed changes with height can be determined, and this information can be used as the wind speed input at the inlet boundary. For turbulence intensity, it can be determined based on empirical formulas or actual measurement data. Usually, turbulence intensity is related to factors such as wind speed and terrain.

[0057] Set the pressure condition and turbulence condition of the outlet boundary. Generally, the outlet boundary is set as a pressure outlet, and the pressure value at the outlet is determined according to the actual situation. For example, the outlet can be assumed to be at atmospheric pressure. For turbulence conditions, it can be set to a zero gradient turbulence boundary condition, that is, the turbulence characteristics at the outlet are continuous with the turbulence characteristics of the adjacent area.

[0058] Set the wall function and roughness parameters of the ground boundary. Determine the roughness parameters of the ground according to the actual surface conditions of the high slope terrain. For example, it can be determined by measuring the particle size, roughness and other characteristics of the ground. Then select the appropriate wall function, such as the standard wall function and enhanced wall function, to simulate the interaction between the ground and the flow field.

[0059] Set the rotation boundary conditions and damping zones of the wind turbine boundary. For the blades of the wind turbine, set the rotation boundary conditions and set the parameters according to the rotation speed and direction of the blades. Set the damping zone around the wind turbine and adjust the damping coefficient and other parameters to reduce the numerical fluctuation and improve the calculation stability.

[0060] Results: The specific boundary conditions for flow field calculation were determined, including various parameters of the inlet, outlet, ground and wind turbine boundary.

[0061] Step 4: Select the physical model: Consider the characteristics of the wind field under high slope terrain, such as the impact of terrain on wind blocking and acceleration, as well as factors such as the turbulent characteristics of wind, and select a suitable physical model. Common physical models include Reynolds-averaged Navier-Stokes equations (RANS) models, such as the kε model and kω model. If you pursue higher accuracy, you can choose advanced turbulence models, such as large eddy simulation (LES) or detached eddy simulation (DES). For large eddy simulation, it can simulate the large-scale structure of turbulence more accurately, but the computational cost is high; detached eddy simulation combines the advantages of RANS model and LES, and improves accuracy and computational efficiency to a certain extent.

[0062] Results: The specific physical model for flow field calculation was determined, such as kε model, LES or DES.

[0063] Step 5: Parallel computing settings: If you have high-performance computing resources, such as a distributed computing platform (such as an HPC cluster) or a high-performance computing cluster, check the number of computing nodes, number of CPU cores, memory capacity and other hardware resources to ensure that they can meet the needs of parallel computing.

[0064] Use tools such as the MPI parallel computing framework to decompose CFD calculation tasks into multiple subtasks. Determine the division method of subtasks based on the computing resources and the characteristics of flow field calculations, such as division by grid area or by the calculation steps of the physical model.

[0065] The decomposed subtasks are assigned to different computing nodes for parallel computing. Through the communication mechanism of the MPI framework, data exchange and synchronization between computing nodes are realized to ensure the correctness and efficiency of the calculation.

[0066] Results: The numerical simulation calculation process of the flow field was accelerated, which was manifested in the shortening of calculation time and the improvement of calculation efficiency.

[0067] Step 6: Result verification: Set up multiple wind speed measurement points on the high slope terrain, use professional wind speed measurement instruments (such as anemometers, laser radars, etc.) to perform actual measurements, and obtain wind speed and turbulence intensity data at different locations. The locations of the measurement points should cover different areas of the high slope, including key locations such as complex terrain areas and near wind turbines.

[0068] Compare the actual measured data with the simulation results. The comparison indicators include wind speed, wind speed distribution, turbulence intensity, etc. Comparative analysis can be performed by drawing charts, calculating errors, etc.

[0069] If there is a large deviation, analyze the cause of the deviation, which may be unreasonable model parameter settings, inaccurate boundary conditions, inappropriate mesh division, etc. Then adjust the model parameters and calculation settings, such as adjusting the parameters of the physical model, optimizing the mesh density and type, modifying the boundary conditions, etc., and re-simulate the calculation.

[0070] Results: The accuracy of the simulation results was verified, and the specific wind speed distribution and turbulence intensity distribution on the entire wind turbine rotor surface were obtained, including wind speed values, turbulence intensity values ​​and distribution rules at different positions.

[0071] 4. Generate target wind seed file using TurbSim tool Step 1: Parameter analysis: Input: The wind speed distribution and turbulence intensity distribution data obtained by using CFD tools in the third step. Specifically, these data include information such as wind speed size, wind speed direction, and turbulence intensity value at different locations. Through statistical analysis of these data, such as calculating the mean, standard deviation, maximum and minimum values ​​of wind speed, and analyzing the distribution law of turbulence intensity. At the same time, combined with historical meteorological data and the terrain characteristics of high slope areas, understand the characteristics and change laws of the wind field. For example, observe the change law of wind speed with height, seasonal changes in wind direction, etc.

[0072] Results: The parameter characteristics of the actual wind field are obtained, such as average wind speed, wind speed standard deviation, turbulence intensity range, wind direction distribution law, etc.

[0073] Step 2: Parameter optimization: According to the actual wind field conditions, that is, the wind speed, wind direction, turbulence intensity and other data in the high slope area obtained through field measurements, as well as the results of statistical analysis in the first step, the input parameters of TurbSim are optimized. Specifically, the wind speed profile is adjusted, for example, different wind speed variation models with height are selected, such as power law model or logarithmic model, and appropriate parameter values ​​are determined. Turbulence model parameters such as turbulence intensity and turbulence scale are adjusted. At the same time, the random number seed is adjusted to generate different random wind field sequences. The optimal input parameter combination is determined through multiple tests and comparisons.

[0074] Results: The optimized input parameters were determined, including specific wind speed profile parameters, turbulence model parameter values ​​and random number seed values.

[0075] Step 3: Generate a single sample wind seed file: Use the TurbSim tool to set the optimized input parameters determined in step 2 into the tool. During the setting process, carefully check the value of each parameter to ensure accuracy. Then run the tool to generate a wind farm time series file, i.e., wind seed file, based on the input parameters. This file contains information such as wind speed and wind direction over a period of time, simulating the changes in the actual wind farm.

[0076] Results: A representative wind seed file was obtained, which can accurately reflect the wind field characteristics in high slope areas.

[0077] Step 4: Multi-condition simulation: Consider different factors such as wind speed, wind direction, and turbulence intensity. Specifically, determine a series of different wind speed value ranges, such as low wind speed (less than 5m / s), medium wind speed (5m / s10m / s), and high wind speed (greater than 10m / s). For wind direction, consider different dominant wind directions, such as easterly, westerly, southerly, and northerly. For turbulence intensity, determine different intensity levels, such as low turbulence intensity (less than 10%), medium turbulence intensity (10%20%), and high turbulence intensity (greater than 20%). Then, adjust the input parameters multiple times, that is, adjust the input parameters of TurbSim according to different combinations of wind speed, wind direction, and turbulence intensity. For example, for the conditions of low wind speed, easterly wind, and low turbulence intensity, set the corresponding parameter values. Generate multiple wind seed files for different conditions, each corresponding to a specific wind field condition.

[0078] Result: A series of wind seed files covering more wind field conditions are generated, including wind seed files under different combinations of wind speed, wind direction and turbulence intensity.

[0079] Step 5: Automatic generation: The script is written in Python programming language. The functions of the script include automatically reading the wind seed file template generated in the third step and the different working condition parameters determined in the fourth step. Then, the TurbSim tool is automatically called and different parameter settings are passed to the tool. During the call process, command line parameters or the API interface provided by the tool are used to ensure that the parameter settings are accurate. At the same time, the generated wind seed file is automatically named, and the naming rule follows the format of "WindSeed_wind speed value_turbulence intensity value_terrain feature_generation time.bts". For example, for a file with a wind speed of 8m / s, a turbulence intensity of 15%, a terrain feature of "Slope20", and a generation time of "20241023", it is named "WindSeed_8m / s_15%_Slope20_20241023.bts". In addition, the files are classified and stored according to factors such as wind speed, turbulence intensity and terrain characteristics. For example, different folders are created and named as wind speed range folders such as "LowSpeed", "MediumSpeed" and "HighSpeed", and turbulence intensity range folders such as "LowTurbulence", "MediumTurbulence" and "HighTurbulence", and the corresponding wind seed files are stored in the corresponding folders.

[0080] Results: Generate a large number of wind seed files efficiently, and facilitate subsequent management and use. Specifically, a large number of wind seed files for different working conditions can be quickly generated through the script, and the naming and classification storage of the files make it easier to find and use the files later.

[0081] Final result: A series of wind seed files are obtained, providing basic data for the dynamic response analysis of the whole machine.

[0082] 5. Establish a high slope wind file library: Step 1: Develop standardized naming conventions Determine the information contained in the file name, such as wind speed, turbulence intensity, terrain features, generation time, etc. Specifically, wind speed information is in "m / s" and is accurate to one decimal place; turbulence intensity is expressed in percentage form and is accurate to an integer; terrain features are described in concise text, such as "Slope20" means the slope is 20 degrees; generation time is expressed in the format of "year, month, and day".

[0083] Create a specific naming format, such as "WindSeed_wind speed value_turbulence intensity value_terrain feature_generation time.bts". For example, a wind seed file might be named: “WindSeed_8.5m / s_12%_Slope18_20241023.bts” clearly states that the wind speed is 8.5m / s, the turbulence intensity is 12%, the terrain feature is a slope of 18 degrees, and the generation time is October 23, 2024.

[0084] Result: With the unified file naming rules, the naming of wind seed files has clear meaning and standardization.

[0085] Step 2: Classify the wind seed file: Classify wind seed files according to factors such as wind speed range, turbulence intensity range, and terrain characteristics. Specifically, the wind speed range can be divided into low wind speed (less than 5m / s), medium wind speed (5m / s10m / s), and high wind speed (greater than 10m / s); the turbulence intensity range can be divided into low turbulence intensity (less than 10%), medium turbulence intensity (10%20%), and high turbulence intensity (greater than 20%); terrain characteristics can be classified according to actual terrain characteristics, such as slope, curvature, etc. For example, create different folders corresponding to different categories, such as "LowSpeed", "MediumSpeed", "HighSpeed" folders corresponding to different wind speed ranges, "LowTurbulence", "MediumTurbulence", "HighTurbulence" folders corresponding to different turbulence intensity ranges, "Slope15", "Slope20" and other folders corresponding to different terrain features.

[0086] Result: The wind seed files are classified and organized to facilitate subsequent management and search.

[0087] Step 3: Name the wind seed file: Name each wind seed file according to the standardized naming rules. During the naming process, carefully check the file's wind speed, turbulence intensity, terrain features, and generation time to ensure that the naming is accurate. For example, if a file has a wind speed of 7.8m / s, a turbulence intensity of 14%, a terrain feature of 16 degrees slope, and a generation time of October 24, 2024, then according to the naming rules, the file is named "WindSeed_7.8m / s_14%_Slope16_20241024.bts".

[0088] Ensure that the file name accurately reflects the characteristic information of the file so that important information such as the wind field conditions and generation time represented by the file can be quickly understood through the file name.

[0089] Result: Each wind seed file has a standardized name, which is easy to manage and use.

[0090] Step 4: Store the wind seed file: In the designated storage location, such as the specially set high slope wind file library folder, the named wind seed files are stored according to the classification. Specifically, the wind seed files of different classifications are stored in the corresponding folders to ensure that the file storage path is clear and easy to manage. For example, the files with a wind speed of 8m / s, a turbulence intensity of 15%, and a terrain feature of a slope of 20 degrees are stored in the three folders "MediumSpeed", "MediumTurbulence", and "Slope20".

[0091] Result: The wind seed file is properly stored, which is convenient for subsequent search and use.

[0092] Step 5: Establish a database management system: Choose a suitable database management system, such as MySQL or SQLite. Specifically, if the amount of data is large and multiple users need to access it at the same time, you can choose MySQL; if the amount of data is small and you want it to be simple and easy to use, you can choose SQLite. Choose according to actual needs, and install and configure the database management system.

[0093] Create a database table to store the information of wind seed files, including file path, wind speed, turbulence intensity, terrain features, etc. For example, create a table named "wind_seed_files" containing fields such as "file_path", "wind_speed", "turbulence_intensity", and "terrain_feature".

[0094] Enter the information of the wind seed file into the database. By writing a script or using a database management tool, enter the information of each wind seed file into the database one by one. For example, for a file with a file path of " / path / to / file / WindSeed_8m / s_15%_Slope20_20241023.bts", enter its file path, wind speed 8m / s, turbulence intensity 15%, terrain feature "Slope20" and other information into the database table.

[0095] Results: A database management system was established to quickly retrieve wind seed file information. Through database query statements, it is easy to quickly find the corresponding wind seed file based on conditions such as wind speed, turbulence intensity, and terrain characteristics.

[0096] Step 6: Implement database query function: Using database query statements, you can quickly retrieve the required wind seed files based on specific conditions. Specifically, use SQL query statements to query based on conditions such as wind speed, turbulence intensity, and terrain features. For example, if you want to find wind seed files with wind speeds of 7m / s8m / s, turbulence intensity of 10%15%, and terrain features with a slope of 18 degrees, you can write the following SQL query statement: "SELECT file_path FROM wind_seed_files WHERE wind_speedBETWEEN 7 AND 8 AND turbulence_intensity BETWEEN 10 AND 15 AND terrain_feature = 'Slope18'".

[0097] Result: The required wind seed files can be easily found from the database, which improves the efficiency of file retrieval.

[0098] Step 7: Use version control tools: Choose a version control tool, such as Git. Install and configure the Git tool, and create a dedicated version control repository for managing wind seed files.

[0099] Whenever a new wind seed file is generated or an existing file is modified, a version control tool is used to record and manage it. Specifically, the newly generated wind seed file is added to the version control repository and a description is submitted, indicating important information such as the file generation time and wind field conditions. Similar operations are performed for modifications to existing files, recording the content and reasons for the modifications.

[0100] Result: The version control of the wind seed file is realized to ensure data traceability. The historical versions of the file can be viewed at any time, the differences between different versions can be compared, and a specific version can be restored when necessary.

[0101] Final result: A high slope wind file library and index file were established to facilitate the management and reuse of wind seed files, improving research efficiency. At the same time, database management and version control were used to improve data security and manageability.

[0102] 6. Calculate the dynamic response of the whole machine: Step 1: Determine the analysis conditions: Input: The high slope wind file library established in step 5. Select different wind seed files from the wind file library to determine the operating conditions to be analyzed. Specifically, according to the design requirements and actual operation of the wind turbine, select wind seed file combinations with different wind speeds, wind directions, and turbulence intensities. For example, you can select a file combination of low wind speed, easterly wind, and low turbulence intensity, and a file combination of high wind speed, westerly wind, and high turbulence intensity. By considering a variety of different operating conditions, you can more comprehensively evaluate the performance of wind turbines under different wind field conditions.

[0103] Result: Multiple analysis cases were identified, each corresponding to a specific set of wind seed files.

[0104] Step 2: Multi-operating condition analysis: Use the Bladed tool to import wind seed files under different working conditions one by one. During the import process, ensure that the file path is correct and the parameters are set accurately. Then, simulate the operation of the wind turbine under different wind field conditions. Through the simulation function of the tool, consider the structural characteristics of the wind turbine, blade rotation and other factors, and simulate the dynamic response of the wind turbine under different wind speeds, wind directions and turbulence intensities.

[0105] Analyze the load changes of wind turbines under different working conditions. Specifically, through the results output by the tool, analyze the various loads that wind turbines are subjected to under different working conditions, such as blade loads, tower loads, etc. You can calculate the average, maximum, minimum and other statistical quantities of the load under different working conditions, and observe the change pattern of the load over time.

[0106] Results: The performance data of wind turbines under various working conditions were obtained, including information such as load size and change rules under different working conditions.

[0107] Step 3: Select the advanced dynamics model: Consider factors such as the nonlinear characteristics and structural flexibility of wind turbines. Specifically, analyze the nonlinear phenomena that may occur during the operation of wind turbines, such as large deformation of blades and vibration of towers. At the same time, consider the flexibility of the wind turbine structure, that is, the structure will deform under the action of force. Based on these factors, determine more complex advanced dynamic models, such as models that can better reflect these characteristics. For example, you can choose a finite element model that considers nonlinear factors and structural flexibility, or use a multi-body dynamics model.

[0108] Result: An advanced dynamic model for calculation was determined, which can more accurately simulate the dynamic response of wind turbines under complex wind field conditions.

[0109] Step 4: Perform dynamic calculations: Use the selected advanced dynamics model and Bladed tool. Use the data in the wind file library as input and combine it with the advanced dynamics model for calculation. During the calculation process, carefully set the model parameters to ensure the accuracy and reliability of the calculation. For example, set parameters such as material properties, boundary conditions, and initial conditions.

[0110] Results: Preliminary dynamic response results were obtained, including displacement, velocity, acceleration, load and other information of wind turbines under different wind field conditions.

[0111] Step 5: Result verification: If there is actual operating data of wind turbines in high slope terrain, specifically, actual operating data such as wind speed, wind direction, load, etc. can be obtained through sensors installed on wind turbines. These actual data are compared with the simulation results to analyze the differences between the two. For example, the error between the simulation results and the actual data is calculated, including absolute error and relative error.

[0112] If there is a large deviation, further adjust the model parameters and calculation settings. Specifically, the cause of the analysis deviation may be unreasonable model parameter settings, inaccurate boundary conditions, inappropriate mesh division, etc. Then, adjust the model parameters according to the analysis results, such as adjusting material properties, increasing mesh density, optimizing boundary conditions, etc., and recalculate.

[0113] Results: The accuracy of the simulation results was verified, and the dynamic response (load results) of the wind turbine under high slope terrain was obtained, providing a basis for the safety, power generation efficiency and service life evaluation of the wind turbine.

[0114] Through the above series of optimization steps, accurate load results of wind turbines under high slope terrain are obtained, which provides a scientific basis for the design optimization of wind turbines and the site selection of wind farms.

[0115] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A CFD-based method for simulating wind turbine loads on high slopes, characterized in that The following steps are involved: Step 1: Obtain high slope terrain data and camera position information: obtain high slope terrain data and camera position information through multi-source data collection; Step 2: Construct a simplified physical model of the high slope based on the high slope terrain data and camera position information; Step 3: Use CFD tools to perform numerical simulation calculations of the flow field: Based on the constructed simplified physical model of the high slope, use CFD tools to obtain the wind speed distribution and turbulence intensity distribution on the entire rotor surface of the wind turbine; Step 4: Generate the target wind seed file using the TurbSim tool; Step 5, establish a high slope wind file library; Step 6: Calculate the dynamic response of the whole machine; obtain the accurate load result of the wind turbine under the high slope terrain.

2. The method for simulating wind turbine loads under high slopes based on CFD according to claim 1, characterized in that: The sub-steps of step 1 are: Step 1.1, multi-source data acquisition: use satellite image acquisition equipment to obtain satellite terrain image data, which contains two-dimensional image information of terrain and corresponding coordinate information; process the satellite terrain image data through remote sensing image processing tools to generate a digital elevation model; Use drone equipment to take aerial photos and obtain drone terrain image data and altitude data; Use total station equipment, GPS equipment and ground measurement equipment to conduct field measurements of high slope terrain to obtain high-precision terrain data points, which contain the coordinate information of the geographical location and elevation information; Step 1.2, perform data fusion: compare the elevation data in the digital elevation model with the ground measurement data obtained by the ground measurement equipment point by point; Identify and remove outliers that significantly deviate from the majority of data points; Obtaining terrain data with higher accuracy and reliability, providing more accurate basic data for the subsequent construction of a simplified physical model of a high slope, wherein the basic data includes terrain elevation information, two-dimensional image information, and coordinate information; Step 1.3: Automated data processing: Use Python modules to automatically read satellite terrain image data, drone terrain image data and altitude data, and ground measurement data; convert data from different sources into a unified data format; at the same time, perform coordinate system unification operations to ensure that the coordinate systems of all data are consistent; finally, integrate the processed data into a database; Step 1.4, perform data verification: re-measure the high slope terrain at different time points and verify the aircraft position information on site; compare the data changes before and after, and update the terrain data in a timely manner; ensure the timeliness and accuracy of the data, and obtain accurate high slope terrain data and aircraft position information.

3. The method for simulating wind turbine loads under high slopes based on CFD according to claim 1, characterized in that: The sub-steps of step 2 are as follows: Step 2.1, determine the scope and scale of the simplified physical model of the high slope: obtain the high slope terrain data and camera position information, where the high slope terrain data includes the elevation information, two-dimensional image information and coordinate information of the terrain; analyze the terrain and camera position information to determine the scope of the terrain area to be simulated; determine the scope and scale of the simplified physical model of the high slope; Step 2.2, generate digital elevation model: using the elevation information in the acquired terrain data, integrating data from different sources, and using geographic information system tools to generate a digital elevation model to reflect the ups and downs of the terrain; The data from different sources include: digital elevation models generated from satellite terrain image data, elevation information generated with the assistance of drone altitude data, and elevation information from ground measurement data; Step 2.3, simplifying terrain features: extracting key terrain features from the digital elevation model, wherein the key terrain features include obtaining slope information by calculating the elevation change rate in the digital elevation model; obtaining curvature information by calculating the curvature of the terrain surface; appropriately simplifying the terrain features according to the actual needs of the wind turbine; Step 2.4: Use the adaptive meshing function in the CFD tool to automatically increase the mesh density to capture details in areas with large terrain changes, steep slopes, and complex curvatures; reduce the mesh density to reduce computing resource consumption in areas with relatively flat terrain and small changes; and finally divide the mesh to adapt to the complexity of the terrain; The CFD tools include ANSYS Fluent and OpenFOAM; Step 2.5, multi-scale modeling: First, build a macroscopic high slope terrain model, and use the digital elevation model and terrain feature information to build the general outline and trend of the overall terrain; determine the overall terrain trend and wind direction distribution, and analyze it in combination with meteorological data and terrain features; conduct micro-modeling in local areas, refine the details of terrain features and wind turbines, and finally establish a multi-scale physical model; Step 2.6, perform model verification: simulate the wind speed distribution under standard wind field conditions, compare it with the theoretical value, and check whether the model can accurately simulate the basic characteristics of the wind field; the theoretical value is calculated by the wind field theory formula; finally, it is used to verify the basic function and accuracy of the model and obtain a simplified physical model of the high slope.

4. The method for simulating wind turbine loads under high slopes based on CFD according to claim 1, characterized in that: The sub-steps of step 3 are: Step 3.1, select CFD tools: determine the specific tools used for flow field numerical simulation calculations, including ANSYS Fluent and OpenFOAM; Step 3.2, meshing: Based on the constructed simplified physical model of the high slope, meshing is performed in the selected CFD tool; specific meshes suitable for flow field calculation are divided, and the specific meshes include mesh density and mesh type in different regions; Step 3.3, set boundary conditions: It includes the following: setting the wind speed distribution and turbulence intensity at the inlet boundary; Set the pressure and turbulence conditions at the outlet boundary; Set the wall function and roughness parameters of the ground boundary; Set the rotation boundary conditions and damping zones at the wind turbine boundary; Step 3.4, select the physical model: Consider the wind field characteristics under the high slope terrain and the turbulent characteristics of the wind, and select a suitable physical model; the wind field characteristics include the blocking and acceleration effects of the terrain on the wind; Step 3.5, set up parallel computing: Use the MPI parallel computing framework tool to decompose the CFD computing task into multiple subtasks; determine the subtask division method based on the computing resources and the characteristics of the flow field calculation; assign the decomposed subtasks to different computing nodes for parallel computing; use the communication mechanism of the MPI framework to achieve data exchange and synchronization between computing nodes to ensure the correctness and efficiency of the calculation; Step 3.6: Verify the results: Compare the actual measurement data with the simulation results to verify the accuracy of the simulation results.

5. The method for simulating wind turbine loads under high slopes based on CFD according to claim 1, characterized in that: The sub-steps of step 4 are as follows: step 4.1, using CFD tools to simulate the wind speed distribution and turbulence intensity distribution data; obtaining parameter characteristics of the actual wind field, the parameter characteristics include average wind speed, wind speed standard deviation, turbulence intensity range, and wind direction distribution law; Step 4.2, perform parameter optimization: optimize the input parameters of TurbSim through the wind speed, wind direction, and turbulence intensity data obtained through field measurements in high slope areas, as well as the results obtained from the statistical analysis in step 4.1; adjust the turbulence model parameters, which include turbulence intensity and turbulence scale; at the same time, adjust the random number seed to generate different random wind field sequences; determine the optimal input parameter combination through multiple tests and comparisons; Step 4.3, generate a single sample wind seed file: use the TurbSim tool to set the optimized input parameters determined in step 4.2 into the TurbSim tool; During the setting process, carefully check the value of each parameter to ensure accuracy; then run the TurbSim tool to generate a wind field time series file, i.e., wind seed file, based on the input parameters; The wind seed file contains the wind speed and direction information over a period of time, simulating the changes in the actual wind field; Step 4.4, multi-condition simulation: determine a series of different wind speed value ranges, the wind speed value ranges include low wind speed, medium wind speed and high wind speed; For wind direction, different dominant wind directions are considered, including easterly, westerly, southerly and northerly; For turbulence intensity, different intensity levels are determined, including low turbulence intensity, medium turbulence intensity and high turbulence intensity; then, the input parameters are adjusted multiple times, that is, the input parameters of TurbSim are adjusted according to different combinations of wind speed, wind direction and turbulence intensity; Step 4.5: Use Python programming tools to generate a large number of wind seed files for different working conditions, and name and classify the files for storage, making it easier to find and use the files later.

6. The method for simulating wind turbine loads under high slopes based on CFD according to claim 1, characterized in that: The sub-steps of step 5 are: Step 5.1: Develop standardized naming rules; Step 5.2, classify the wind seed files according to factors including wind speed range, turbulence intensity range, and terrain characteristics; Step 5.3, name each wind seed file according to the standardized naming rules; Step 5.4, store the wind seed files of different categories into corresponding folders, and ensure that the file storage path is clear and easy to manage; Step 5.5: Establish a database management system.

7. The method for simulating wind turbine loads under high slopes based on CFD according to claim 1, characterized in that: The sub-steps of step 6 are: Step 6.1, determine the analysis conditions: select different wind seed files from the wind file library to determine the conditions to be analyzed; each condition corresponds to a set of specific wind seed files; Step 6.2, conduct multi-condition analysis: Use the Bladed tool to import wind seed files under different working conditions in turn; during the import process, ensure that the file path is correct and the parameter settings are accurate; then, simulate the operation of the wind turbine under different wind field conditions; through the simulation function of the Bladed tool, consider the structural characteristics of the wind turbine and the blade rotation factors, simulate the dynamic response of the wind turbine under different wind speeds, wind directions and turbulence intensities; analyze the load changes of the wind turbine under different working conditions; obtain the performance data of the wind turbine under various working conditions, including the load size and change law under different working conditions; Step 6.3, select the advanced dynamics model: analyze the nonlinear phenomena that may occur during the operation of the wind turbine, including large deformation of the blades and vibration of the tower; at the same time, consider the flexibility of the wind turbine structure, that is, the structure will deform under the action of force; finally determine a more complex advanced dynamics model; Step 6.4, perform dynamic calculation: use the selected advanced dynamic model and Bladed tool; use the data in the wind file library as input, and perform calculation in combination with the advanced dynamic model; obtain preliminary dynamic response results, which include the displacement, velocity, acceleration, and load information of the wind turbine under different wind field conditions; Step 6.5, result verification: obtain actual operation data through sensors installed on the wind turbine, including wind speed, wind direction, and load information; These actual data are compared with the simulation results to analyze the differences between the two; if there is a large deviation, the model parameters and calculation settings are further adjusted; the accuracy of the simulation results is verified, and the dynamic response of the wind turbine under high slope terrain is obtained; the accurate load results of the wind turbine under high slope terrain are obtained.

8. The method for simulating wind turbine loads under high slopes based on CFD according to claim 4, characterized in that: In step 3.2, the criteria for meshing are: (1) The complexity of the high-slope terrain is evaluated. Areas with dramatic terrain changes, steep slopes, and complex curvatures are considered to be areas of high complexity. For areas of high complexity, a finer grid density is used. The finer grid density refers to setting the grid size to a smaller value to more accurately capture terrain details and flow field changes. (2) For areas with relatively flat terrain and less variation, a coarser grid density is used to reduce the consumption of computing resources; (3) Select an appropriate grid type based on the computational accuracy requirements. Grid types include structured grids and unstructured grids. If you need to accurately simulate a regular-shaped area, select a structured grid. For complex terrain, choose unstructured grid.

9. The method for simulating wind turbine loads under high slopes based on CFD according to claim 4, characterized in that: In step 3.6, the actual measured data is compared with the simulation results to verify the accuracy of the simulation results, including: (1) Set up multiple wind speed measurement points on the high slope terrain, use wind speed measuring instruments to conduct actual measurements, and obtain wind speed and turbulence intensity data at different locations; the locations of the measurement points should cover different areas of the high slope, including key locations such as areas with complex terrain and near wind turbines; (2) Compare the actual measured data with the simulation results; the comparison indicators include wind speed, wind speed distribution, and turbulence intensity; perform comparative analysis by drawing charts and calculating errors; (3) If there is a large deviation, analyze the cause of the deviation, which may include unreasonable model parameter settings, inaccurate boundary conditions, and inappropriate mesh division; Then adjust the model parameters and calculation settings, including adjusting the parameters of the physical model, optimizing the mesh density and type, modifying the boundary conditions, and finally re-simulating the calculation; (4) The accuracy of the simulation results was verified, and the specific wind speed distribution and turbulence intensity distribution on the entire wind turbine rotor surface were obtained. The specific wind speed distribution and turbulence intensity distribution included wind speed values, turbulence intensity values ​​and distribution patterns at different locations.

10. A CFD-based wind turbine load simulation system under high slopes, characterized by: A CFD-based wind turbine load simulation method for high slopes according to any one of claims 1 to 9 is adopted; comprising: Acquisition unit: used to obtain high slope terrain data and camera position information: high slope terrain data and camera position information are obtained through multi-source data acquisition methods; Modeling unit: used to construct a simplified physical model of the high slope based on the high slope terrain data and aircraft position information; Simulation unit: including CFD tools, using CFD tools to perform numerical simulation calculations of flow fields: based on the constructed simplified physical model of high slopes, using CFD tools to obtain the wind speed distribution and turbulence intensity distribution on the entire rotor surface of the wind turbine; Storage unit: Generate target wind seed files using TurbSim tool; Establish high slope wind file library; Result input unit: used to calculate the dynamic response of the whole machine; to obtain accurate load results of wind turbines under high slope terrain.

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