Flow field acceleration factor correction method, device and equipment based on multi-point short-term wind measurement data and storage medium

Abstract

The invention provides a flow field acceleration factor correction method, device and equipment based on multi-point short-term wind measurement data and a storage medium, and relates to the technical field of wind power plants. The method comprises the following steps: acquiring a flow field acceleration factor of each grid point in a flow field space, and acquiring wind measurement data of each sector of a wind measurement point; performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstruction acceleration factor of a flow field reconstruction grid point; performing data assimilation processing on the wind measurement data of each sector of the wind measurement point, and determining a reference acceleration factor of each sector of the wind measurement point; and based on the reference acceleration factor and the reconstruction acceleration factor, carrying out correction processing on the flow field acceleration factor to obtain a target correction acceleration factor. According to the embodiment provided by the invention, the acceleration factor is corrected by using the multi-point short-term wind measurement data, the accuracy of generation of the acceleration factor can be improved, the error of the acceleration factor is reduced, and the accuracy of calculation of the wind speed in the flow field is ensured by correcting the error of the flow field model.

Description

Technical Field

[0001] The present invention relates to the technical field of wind farms, and in particular to a method, device, equipment and storage medium for correcting a flow field acceleration factor based on multi-point short-term wind measurement data. Background Art

[0002] During the early development of wind power projects, a CFD or WRF flow field model needs to be established for complex mountain wind farms. The acceleration factor of any spatial point in the flow field is obtained through CFD or WRF simulation. Due to certain deviations in input files such as wind farm terrain, roughness and thermal stability, the acceleration factor obtained by CFD or WRF simulation of complex mountain wind farms has certain errors, resulting in errors in the wind speed calculation of the wind farm in the later stage.

[0003] In the related art, there is no disclosure on how to solve the problem of the error of the acceleration factor. How to reduce the error of the acceleration factor is a technical problem that needs to be solved urgently. Summary of the invention

[0004] The present invention provides a flow field acceleration factor correction method, device, equipment and storage medium based on multi-point short-term wind measurement data, which is used to solve the defect that the acceleration factor generated in the prior art has errors. By using multi-point short-term wind measurement data to correct the acceleration factor, the accuracy of the acceleration factor generation can be improved and the error of the acceleration factor can be reduced.

[0005] In a first aspect, the present invention provides a method for correcting a flow field acceleration factor based on multi-point short-term wind measurement data, comprising the following steps: Obtain the flow field acceleration factor of each grid point in the flow field space, and obtain the wind measurement data of each sector of the wind measurement point; Performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; Performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; Based on the reference acceleration factor and the reconstructed acceleration factor, the flow field acceleration factor is corrected to obtain a target corrected acceleration factor.

[0006] Preferably, according to a flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the present invention, the flow field acceleration factor is corrected based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor, including: Acquire an initial flow field acceleration factor, and calculate a difference between the reference acceleration factor and the reconstructed acceleration factor to obtain an acceleration factor difference; Determine whether the acceleration factor difference is less than a preset difference threshold; If yes, the initial flow field acceleration factor is used as the target correction acceleration factor; If not, the reference acceleration factor, the reconstruction acceleration factor, and the initial flow field acceleration factor are calculated using the acceleration factor correction formula to obtain a new correction acceleration factor; the new correction acceleration factor is reconstructed to generate a new reconstruction acceleration factor; and the difference between the reference acceleration factor and the new reconstruction acceleration factor is calculated to obtain a new acceleration factor difference; Determine whether the new acceleration factor difference is less than the preset difference threshold; If not, the following steps are executed cyclically: using the acceleration factor correction formula, calculating the reference acceleration factor, the new reconstructed acceleration factor, and the corrected acceleration factor obtained in the previous cycle to obtain a new corrected acceleration factor; reconstructing the new corrected acceleration factor to generate a new reconstructed acceleration factor; calculating the difference between the reference acceleration factor and the new reconstructed acceleration factor to obtain a new acceleration factor difference; and determining whether the new acceleration factor difference is less than the preset difference threshold; If so, the loop is stopped, and the new modified acceleration factor corresponding to the current loop round is used as the target modified acceleration factor.

[0007] Preferably, according to a flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the present invention, the wind measurement data of each sector of the wind measurement point is subjected to data assimilation processing to determine a reference acceleration factor of each sector of the wind measurement point, including: Preprocessing the wind measurement data of each sector of the wind measurement point to obtain preprocessed wind measurement data; the preprocessed wind measurement data includes wind speed data and wind direction data; The wind speed data and the wind direction data of each sector of the wind measuring point are calculated and processed to obtain a reference acceleration factor of each sector of the wind measuring point.

[0008] Preferably, according to a flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the present invention, the wind measurement data of each sector of the wind measurement point is preprocessed to obtain preprocessed wind measurement data, including: Performing highly unified calculation processing on the wind measurement data of each sector of the wind measurement point to obtain short-term wind measurement data of a unified height; The short-term wind measurement data at the uniform height are subjected to time interpolation processing to obtain the pre-processed wind measurement data at the same time.

[0009] Preferably, according to a flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the present invention, the reference acceleration factor includes: a first equivalent acceleration factor, a second equivalent acceleration factor; The calculating and processing the wind speed data and the wind direction data of each sector of the wind measuring point to obtain a reference acceleration factor of each sector of the wind measuring point includes: Calculating and processing the wind speed data and the wind direction data of each sector of the wind measuring point to obtain a wind speed vector average value; Splitting and calculating the average value of the wind speed vector to obtain a first wind speed vector and a second wind speed vector; The first wind speed vector and the second wind speed vector are subjected to wind speed conversion processing to obtain the first equivalent acceleration factor and the second equivalent acceleration factor.

[0010] Preferably, according to a flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the present invention, the flow field acceleration factor of each grid point in the flow field space is obtained, including: Performing flow field modeling processing on the wind farm area to obtain the flow field space of the wind farm area; The flow field acceleration factor of each grid point in each sector is obtained from the flow field space using a data linear interpolation algorithm.

[0011] In a second aspect, the present invention also provides a flow field acceleration factor correction device based on multi-point short-term wind measurement data, comprising the following modules: An acquisition module is used to obtain the flow field acceleration factor of each grid point in the flow field space, and to obtain the wind measurement data of each sector of the wind measurement point; A reconstruction module, used for performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; A determination module, used to perform data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; The correction module is used to correct the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor.

[0012] In a third aspect, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a flow field acceleration factor correction method based on multi-point short-term wind measurement data as described above is implemented.

[0013] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a flow field acceleration factor correction method based on multi-point short-term wind measurement data as described in any one of the above.

[0014] In a fifth aspect, the present invention further provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-described methods for correcting a flow field acceleration factor based on multi-point short-term wind measurement data.

[0015] The present invention provides a method, device, equipment and storage medium for correcting flow field acceleration factors based on multi-point short-term wind measurement data, which obtains the flow field acceleration factor of each grid point in the flow field space and the wind measurement data of each sector of the wind measurement point; performs wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain the reconstructed acceleration factor of the flow field reconstruction grid point; performs data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine the reference acceleration factor of each sector of the wind measurement point; and corrects the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain the target corrected acceleration factor. The method is used to solve the defect of the acceleration factor having errors in the prior art, and realizes that the acceleration factor can be corrected by using multi-point short-term wind measurement data, so as to improve the accuracy of the acceleration factor generation and reduce the errors in the acceleration factor, and ensure the accuracy of the wind speed estimation in the flow field by correcting the errors of the flow field model. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of a flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the present invention.

[0018] Figure 2 It is a sector schematic diagram of the fitting terrain data provided by the present invention.

[0019] Figure 3 It is a structural schematic diagram of a flow field acceleration factor correction system based on multi-point short-term wind measurement data provided by the present invention.

[0020] Figure 4 It is a structural schematic diagram of a flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention.

[0021] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] First, several nouns involved in the present invention are analyzed: Acceleration Factor: It is a dimensionless parameter used in accelerated life testing to measure the ratio of the product's life characteristics under accelerated stress conditions to those under normal stress conditions.

[0024] CFD flow field model: CFD flow field model is a mathematical model used to describe and simulate fluid flow in computational fluid dynamics (CFD). These models use numerical methods to solve the governing equations of fluid motion to reveal the physical laws and characteristics of fluid motion.

[0025] In the related art, there are at least the following technical problems: The actual wind measurement data can reflect the relationship between the acceleration factors between different grid points within the flow field. The acceleration factors obtained by CFD simulation of complex mountain wind farms can be corrected through multi-point short-term actual wind measurement data.

[0026] In the early design stage of a wind farm, especially in mountainous wind farms where the wind speed varies greatly, it is necessary to simulate the wind speed distribution in the wind farm, and then arrange wind turbines in areas with better wind speeds according to the wind speed distribution. The main problems of this method are as follows: (1) The wind speed assessment at the position close to the wind tower is relatively accurate, but the wind speed at the position far from the wind tower is usually too high or too low.

[0027] (2) Due to limited development funds in the early stage, wind towers could only be built in representative areas. Based on the wind measurement data, the wind speed in a limited area of ​​the wind farm could only be calibrated, and the acceleration factor in the wind farm area did not change; (3) Based on the same acceleration factor in the CFD simulation flow field, the calibration results using data from different wind towers are inconsistent, that is, the wind speeds derived from the wind towers cannot correspond to each other. Combine the following Figure 1-Figure 5The present invention describes a flow field acceleration factor correction method, device, equipment and storage medium based on multi-point short-term wind measurement data, which can improve the accuracy of acceleration factor generation and reduce the error of acceleration factor by using multi-point short-term wind measurement data, and then correct the acceleration factor of the CFD model, further improving the accuracy of wind speed estimation in the wind farm.

[0028] Figure 1 FIG. 1 is a flow chart of a method for correcting flow field acceleration factor of short-term wind measurement data at multiple points provided by the present invention. Figure 1 As shown, the method may include but is not limited to steps S100 to S400: S100, obtaining a flow field acceleration factor for each grid point in the flow field space, and obtaining wind measurement data for each sector of the wind measurement point; S200, performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; S300, performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; S400: Based on the reference acceleration factor and the reconstructed acceleration factor, the flow field acceleration factor is corrected to obtain a target corrected acceleration factor.

[0029] In step S100 of some embodiments, the flow field acceleration factor of each grid point in the flow field space is obtained, and the wind measurement data of each sector of the wind measurement point is obtained.

[0030] It is understandable that in order to accurately estimate the wind speed in a wind farm, it is necessary to use multi-point wind measurement data to correct the acceleration factor of the CFD model in the wind farm, thereby improving the accuracy of the wind speed estimation in the wind farm.

[0031] The specific execution steps for obtaining the flow field acceleration factor of each grid point in the flow field space can be to first perform flow field modeling on the wind farm area to obtain the flow field space of the wind farm area, and then use a data linear interpolation algorithm to obtain the flow field acceleration factor of each grid point in each sector from the flow field space.

[0032] Specifically, a CFD model is performed on the wind farm area to obtain a gridded flow field space of the wind farm area.

[0033] CFD flow field models are mathematical models used to describe and simulate fluid flow in computational fluid dynamics (CFD). These models use numerical methods to solve the governing equations of fluid motion to reveal the physical laws and characteristics of fluid motion.

[0034] The data linear interpolation algorithm is a method used in CNC systems to calculate and generate tool or workpiece motion trajectories. It approximates the ideal contour by inserting a series of intermediate points between known starting and end points.

[0035] The data linear interpolation algorithm specifically includes: Point-by-point comparison method: This is a basic interpolation algorithm. Its core idea is to compare the current position with the target straight line at each step to determine the next moving direction and distance. This method continuously compares the deviation between the current position of the tool and the given straight line, and adjusts the feed direction accordingly, so that the tool gradually approaches the target straight line.

[0036] Digital integration method (DDA): Also known as digital differential analysis, this method calculates the motion trajectory of the tool by simulating the integration process. It takes speed and time as input, calculates the displacement by integration, and thus determines the movement path of the tool. The digital integration method has the advantages of fast calculation speed and easy realization of multi-coordinate linkage, but certain measures need to be taken to meet the interpolation accuracy requirements.

[0037] Data sampling method: also known as time division method, it uses a series of tiny straight line segments connected end to end to approximate a given curve. This method first divides the given contour trajectory into several tiny line segments according to the programming speed and interpolation cycle, and then performs secondary interpolation on these line segments, i.e., fine interpolation, to achieve higher approximation accuracy.

[0038] Direct Function Calculation (DFB): This is an algebraic operation method that divides each quadrant of the rectangular coordinate system into two areas with a line of a specific slope and interpolates in these areas using different feed directions. The DFB method approximates the trajectory by directly calculating the displacement of the tool in each interpolation cycle.

[0039] The embodiment of the present invention can adopt any one of the above data linear interpolation algorithms according to requirements.

[0040] Furthermore, in an embodiment of the present invention, the fluid space in the wind farm area is gridded (the grid spacing is: 30m 30m 30m), and then obtain the horizontal acceleration factor (U, V, ignoring the Z direction) of each grid point in each sector from the CFD flow field model through the data linear interpolation algorithm, and reconstruct the unstructured acceleration factor of the flow field model into the process structured acceleration factor, that is, the flow field acceleration factor of each grid point in each sector.

[0041] 1. Set the flow field area boundary: Set the minimum and maximum values ​​of the X, Y, and Z coordinates of the flow field area grid points, and set the resolution of the flow field area grid points (assuming it is 30m).

[0042] It should be noted that (1) the difference between the maximum and minimum values ​​of grid points X and Y is an integer multiple of 30 m; (2) The minimum value of the grid point Z coordinate is the integer value with the lowest altitude in the wind farm range, i.e., Int(Zmin), and the maximum value of the grid point Z coordinate is the sum of the integer value with the highest altitude in the wind farm range and 500 m, i.e., (Zmax+500 m).

[0043] 2. Get the original acceleration factor: Since the actual wind direction number is 0-360°, for the convenience of calculation, the 360° wind direction is usually divided into 12 or 16 sectors. A flow field model is established in each sector. The acceleration factor of each sector at the same position is different, so it is necessary to extract the flow field acceleration factor according to the sector, and the boundary of the refined area of ​​the flow field should be as large as possible. The flow field area boundary set above.

[0044] 3. Calculate the flow field acceleration factor at the grid point: Considering the spatial geometry, any grid point is within the hexahedron or tetrahedron composed of the original grid points of the CFD flow field. Therefore, the space can be divided into 8 regions with the new grid point as the center. The original acceleration factor grid point with the smallest distance is calculated in each spatial region. Then, the acceleration factor of each sector of the new grid point is obtained according to the linear weighted method. The specific acceleration factor formula of a sector is as follows: (1.1) (1.2) (1.3) Where: is the acceleration factor in the X direction of the new grid; is the acceleration factor in the Y direction of the new grid point; is the acceleration factor in the X direction of the original grid point; is the acceleration factor in the Y direction of the original grid point; is the distance between the original grid point and the new grid point; is the weight coefficient of the original grid point relative to the new grid point (the denominator is +0.1m to prevent it from being 0, when only one original grid point is queried and the original grid point coincides with the new grid point, the distance d=0); To divide the space into 8 regions with the new grid point as the center, the number of original grid points can be queried (n≦8); It should be further explained that when the Z value of the new grid point is lower than the altitude, it is meaningless because the fluid area is above the surface, so the value of these new grid points is set to "null".

[0045] In step S200 of some embodiments, the flow field acceleration factor of each grid point in the flow field space is subjected to wind measurement point sector reconstruction processing to obtain a reconstructed acceleration factor of the flow field reconstruction grid point.

[0046] It can be understood that the flow field acceleration factor of each grid point in the flow field space is subjected to wind measurement point sector reconstruction processing to obtain a reconstructed acceleration factor of the flow field reconstruction grid point.

[0047] It should be further explained that the flow field reconstruction grid can be understood as: converting the flow field grid into a structured grid, that is, 30 30 30 regular hexahedral grid. The original flow field grid is set as an unstructured grid in order to fit the terrain and reduce the amount of calculation. That is, the grid sizes are different and there are distorted grids, which is not convenient for subsequent interpolation operations.

[0048] Since the wind measurement point and the grid points reconstructed in the flow field do not necessarily coincide, the linear interpolation method is used to calculate the reconstruction acceleration factor at the wind measurement point. This scheme is calculated according to the above formulas 1.1-1.3. The difference is that the reconstruction reference data this time is a structured grid point. Each wind tower point has a reference point in the 8 directions of the space. In this way, the reconstruction acceleration factor of each sector at the wind measurement point can be obtained. and .

[0049] In step S300 of some embodiments, data assimilation processing is performed on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point.

[0050] It can be understood that the specific execution step may be to pre-process the wind measurement data of each sector of the wind measurement point to obtain pre-processed wind measurement data.

[0051] It should be noted that the pre-processed wind measurement data includes wind speed data and wind direction data.

[0052] Furthermore, the wind measurement data of each sector of the wind measurement point is subjected to highly unified calculation processing to obtain short-term wind measurement data of uniform height.

[0053] An embodiment of performing highly unified calculation processing on the wind measurement data of each sector of the wind measurement point to obtain short-term wind measurement data of uniform height may specifically be: Due to the influence of terrain and measuring equipment, the surface wind measurement height is diverse. In order to realize the correction of the acceleration factor of flow field reconstruction, the wind measurement data needs to be extrapolated to the same height according to the sector. Usually, the power exponential function is used for calculation. The formula is as follows.

[0054] (2.1) (2.2) In the formula: Specify the location of short-term wind data points Wind speed at altitude; It is the actual measurement at the location of multiple wind measurement data points Wind speed at altitude; It is the actual measurement at the location of multiple wind measurement data points Wind speed at altitude; is the wind shear at the short-term wind measurement data point.

[0055] Furthermore, the short-term wind measurement data at the uniform height are subjected to time interpolation processing to obtain the pre-processed wind measurement data at the same time.

[0056] An embodiment of performing time interpolation processing on the short-term wind measurement data of the uniform height to obtain the pre-processed wind measurement data of the same time may specifically be: Since wind measurement data may have different wind years and different wind months, short-term wind measurement data at multiple points may not overlap in time. Therefore, it is necessary to extend the short-term data of multiple points to the same time period based on long-term wind tower data or mesoscale data. Only by using the wind speed ratio in the same time period can the accurate acceleration factor be obtained. The specific wind speed and direction interpolation formula is as follows: (2.3) In the formula: It is long-term wind tower data or mesoscale data wind speed; Wind speed of short-term wind measurement data at multiple points; The wind speed value for 10 minutes during the overlapping period of long-term wind tower data or mesoscale data; The average wind speed during the period of overlap between long-term wind tower data or mesoscale data; The wind speed value for 10 minutes during the overlapping period of short-term wind measurement data at multiple points; It is the average wind speed during the period of overlap of the short-term wind measurement data at the point.

[0057] (2.4) In the formula: Wind direction for long-term wind tower data or mesoscale data; Wind direction for short-term wind measurement data at multiple points; The wind direction value for 10 minutes during the overlapping period of long-term wind tower data or mesoscale data; It is the wind direction value of 10 minutes during the overlapping period of short-term wind measurement data at multiple points; n is the number of 10-minute wind directions in the overlapping time period between the long-term wind tower data or mesoscale data and each short-term wind measurement data.

[0058] In some embodiments, the wind speed data and the wind direction data of each sector of the wind measuring point are calculated and processed to obtain a reference acceleration factor of each sector of the wind measuring point.

[0059] It should be noted that the reference acceleration factor includes: a first equivalent acceleration factor and a second equivalent acceleration factor.

[0060] The step of calculating and processing the wind speed data and the wind direction data of each sector of the wind measuring point to obtain the reference acceleration factor of each sector of the wind measuring point may specifically be: First, the wind speed data and the wind direction data of each sector of the wind measuring point are calculated and processed to obtain an average wind speed vector, and then the average wind speed vector is split and calculated to obtain a first wind speed vector and a second wind speed vector. Finally, the first wind speed vector and the second wind speed vector are converted into wind speeds to obtain the first equivalent acceleration factor and the second equivalent acceleration factor.

[0061] Furthermore, since the wind data at the short-term wind measurement point is time series data containing two variables, wind speed and wind direction, that is, wind speed data and wind direction data, in order to match the later correction calculation, the wind speed time series data needs to be divided into 16 sectors, but the wind direction of each sector is also different (according to the 16-sector division, the maximum wind direction difference within the sector is close to 22.5°). To address this problem, the wind speed data can be first classified according to the wind direction interval, and then the wind speed and wind direction are considered in a certain sector. The formula for calculating the average wind speed vector is as follows: (2.5) In the formula: is the wind speed vector in a sector at the short-term wind measurement point; n is the number of short-term wind measurement data in a sector; is the average wind speed vector in a sector at a short-term wind measurement point; From the above, we can know that the horizontal acceleration factor has two components in a certain sector, so this time we can use the average wind speed vector in a certain sector as Split into and , the specific formula is as follows: (2.6) (2.7) (2.8) In the formula: is the X-direction component of the wind speed in a sector at the short-term wind measurement point (the X-direction is parallel to the central axis of the sector), that is, the first wind speed vector; is the Y-direction component of the wind speed in a sector at the short-term wind measurement point (the Y-direction is the direction perpendicular to the central axis of the sector), that is, the second wind speed vector; is the average wind speed vector in a sector at a short-term wind measurement point; α is the wind speed vector angle; β is the central axis angle of a sector.

[0062] An embodiment of performing wind speed conversion processing on the first wind speed vector and the second wind speed vector to obtain the first equivalent acceleration factor and the second equivalent acceleration factor may be: Since the value of the flow field model after wind farm reconstruction is the acceleration factor, and the value of the multi-point wind measurement data is the wind speed, the wind speed needs to be converted into a reference acceleration factor to modify the value of the reconstructed flow field model. This time, the wind speed is converted into a reference acceleration factor. The calculation method of the equivalent acceleration factor at the wind measurement point is as follows: (3.1) (3.2) In the formula: is the equivalent acceleration factor in the X direction of the i-th sector at the wind measurement point (the X direction is parallel to the central axis of the sector); is the Y-direction equivalent acceleration factor of the i-th sector at the wind measurement point (the Y-direction is the direction perpendicular to the central axis of the sector); is the X-direction component of the wind speed in a sector at the short-term wind measurement point (the X-direction is parallel to the central axis of the sector), which is the first equivalent acceleration factor; is the Y-direction component of the wind speed in a sector at the short-term wind measurement point (the Y-direction is the direction perpendicular to the central axis of the sector), which is the second equivalent acceleration factor; For sectors.

[0063] In step S400 of some embodiments, the flow field acceleration factor is corrected based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor.

[0064] The specific execution steps of step S400 may be: Acquire an initial flow field acceleration factor, and calculate a difference between the reference acceleration factor and the reconstructed acceleration factor to obtain an acceleration factor difference; Determine whether the acceleration factor difference is less than a preset difference threshold; If yes, the initial flow field acceleration factor is used as the target correction acceleration factor; If not, the reference acceleration factor, the reconstruction acceleration factor, and the initial flow field acceleration factor are calculated using the acceleration factor correction formula to obtain a new correction acceleration factor; the new correction acceleration factor is reconstructed to generate a new reconstruction acceleration factor; and the difference between the reference acceleration factor and the new reconstruction acceleration factor is calculated to obtain a new acceleration factor difference; Determine whether the new acceleration factor difference is less than the preset difference threshold; If not, the following steps are executed cyclically: using the acceleration factor correction formula, calculating the reference acceleration factor, the new reconstructed acceleration factor, and the corrected acceleration factor obtained in the previous cycle to obtain a new corrected acceleration factor; reconstructing the new corrected acceleration factor to generate a new reconstructed acceleration factor; calculating the difference between the reference acceleration factor and the new reconstructed acceleration factor to obtain a new acceleration factor difference; and determining whether the new acceleration factor difference is less than the preset difference threshold; If so, the loop is stopped, and the new modified acceleration factor corresponding to the current loop round is used as the target modified acceleration factor.

[0065] It can be understood that the first cycle: calculate the reference acceleration factor at each sector wind measurement point ( and ) and the reconstruction acceleration factor ( and ) to obtain the acceleration factor difference.

[0066] The acceleration factor difference is compared with a preset difference threshold to determine whether the acceleration factor difference is less than the preset difference threshold. The preset difference threshold may be 0.001.

[0067] If the acceleration factor difference is less than the preset difference threshold, the initial flow field acceleration factor is used as the target correction acceleration factor.

[0068] If the acceleration factor difference is not less than the preset difference threshold, the reference acceleration factor ( and ), the reconstruction acceleration factor ( and ), the initial flow field acceleration factor ( and ) is calculated to obtain the new modified acceleration factor ( and ).

[0069] And the new modified acceleration factor ( and ) to perform reconstruction processing and generate a new reconstruction acceleration factor ( and ).

[0070] Second cycle: Calculate the reference acceleration factor ( and ) and the new reconstruction acceleration factor ( and ) to obtain the new acceleration factor difference.

[0071] Determine whether the new acceleration factor difference is less than the preset difference threshold; If not, the loop executes the acceleration factor correction formula to modify the reference acceleration factor ( and ), the new reconstruction acceleration factor ( and ), the modified acceleration factor obtained in the previous cycle ( and ) is calculated to obtain the new modified acceleration factor ( and ), and the new modified acceleration factor and Perform reconstruction processing to generate a new reconstruction acceleration factor and ; and calculate the reference acceleration factor ( and ) and the new reconstruction acceleration factor ( and ), to obtain a new acceleration factor difference; and a step of determining whether the new acceleration factor difference is less than the preset difference threshold; If so, stop the loop and set the new modified acceleration factor ( and ) as the target correction acceleration factor.

[0072] The specific acceleration factor correction formula is as follows (where n is the number of corrections); Cycle correction 1st time: (3.3) (3.4) (3.5) (3.6) = - (3.7) = - (3.8) Cycle correction 2: ••• ••• (3.9) In the formula: The initial value of the X-direction acceleration factor for the flow field reconstruction grid; The initial value of the Y direction of the grid acceleration factor for flow field reconstruction; The value of the nth cycle of the grid acceleration factor for flow field reconstruction; is the weighted difference in the X direction; is the weighted difference in Y direction; is the difference between the reference acceleration factor in the X direction at the wind measuring point and the reconstructed acceleration factor (e.g., = - ); is the difference between the reference acceleration factor and the reconstructed acceleration factor in the Y direction at the wind measurement point (e.g., = - ); is the distance weight coefficient between the wind measurement point and the flow field reconstruction grid point; is the distance between the wind measurement point and the flow field reconstruction grid; is the search radius of wind measuring points for the reconstructed grid (only wind measuring points within the search radius are used to correct the flow field reconstruction grid).

[0073] The embodiment of the present invention improves the accuracy of acceleration factor generation by using multi-point short-term wind measurement data to correct the acceleration factor, greatly reduces the error of the acceleration factor, and ensures the accuracy of wind speed calculation in the flow field by correcting the error of the flow field model.

[0074] Figure 2 It is a sector schematic diagram of the fitting terrain data provided by the present invention.

[0075] In an embodiment of the present invention, since the local terrain of a complex mountain wind farm may cause drastic changes in wind parameters, whether the short-term wind measurement data is representative requires detailed analysis, and severe shielding areas and wind trap areas need to be avoided. This embodiment uses terrain complexity to determine the representativeness of short-term wind measurement data.

[0076] A plane that conforms to the terrain is defined within a specific distance and sector amplitude in all wind direction sectors around the wind measuring point (see the figure below). The terrain resolution used for terrain complexity assessment does not exceed 50m, and the angle between sectors is not less than 30°. The two indices for judging terrain complexity are TSI (terrain slope index) and TVI (terrain change index).

[0077] TSI is the angular change of a fitted plane that conforms to the terrain over a specific distance and sector.

[0078] Fits the variation in distance along a vertical line between a plane and a surface point for each sector.

[0079] Based on the defined slope and terrain variation, the terrain slope index (TSI) and terrain variation index (TVI) of each circular area are calculated using the following formulas: In the formula, Representatives from The share of wind energy in the sector; represent The slope of the sector fitting surface; The slope of the circular fitting plane; represent Standard deviation of variation in sector areas; represent Standard deviation of the variation in the circular area; R is the radius of the circular area, for The experience adjustment factor of =5 / 3; for The experience adjustment factor of =3.

[0080] The evaluation method for terrain complexity of wind measuring points is shown in Table 1. When the TSI and TVI values ​​are both less than or equal to L, the terrain is considered not complex and the representativeness of the wind measuring point is relatively good; otherwise, the terrain is relatively complex and the representativeness of the wind measuring point is poor, and it is necessary to consider whether to adopt it.

[0081] Table 1:

[0082] Figure 3 It is a structural schematic diagram of a flow field acceleration factor correction system based on multi-point short-term wind measurement data provided by the present invention.

[0083] The embodiment of the present invention also provides a flow field acceleration factor correction system based on multi-point short-term wind measurement data, which mainly includes the following modules: acceleration factor reconstruction module, wind tower data assimilation module, acceleration factor correction module, wind speed estimation module, the system is specifically used for simulating and obtaining flow field acceleration factors, and gridding and sectorizing acceleration factors based on geographic coordinates; assimilation processing and representative analysis of reference wind measurement data; assimilation processing of acceleration factors, converting reference wind measurement data into reference acceleration factors; based on the weights of sectors and spatial distances, correcting flow field acceleration factors. The present invention uses actual wind measurement data to correct the acceleration factor of the flow field according to the sector and distance weights, thereby improving the accuracy of the correction of the acceleration factor.

[0084] The wind speed calculation module of the embodiment of the present invention calculates the modified acceleration factor by: (1) first preparing the time series data and coordinate points of the long-term wind measurement data; (2) using the flow field reconstruction grid point acceleration factor to calculate the 16-sector acceleration factor at the long-term wind measurement data point; (3) setting the target point, using the flow field reconstruction grid point acceleration factor to calculate the 16-sector acceleration factor at the target point; (4) using the time series method, the wind speed and wind direction at each moment of the long-term wind measurement data are multiplied by the ratio of the acceleration factor of the target point to the wind measurement point, so as to obtain the time series data of the target point.

[0085] The embodiments of the present invention can at least achieve the following technical effects: 1. It can better solve the problem of insufficient representation of wind towers, which leads to high and low push in uncertain areas of wind farms; 2. Whether using multiple towers or a single tower, the wind speed results of the target point are consistent (in engineering applications, only one long-term wind measurement tower is needed in an area, and multiple short-term wind measurements are used in areas with uncertain wind speeds, thereby saving the initial investment cost of wind measurement towers); 3. Reconstruct the flow field acceleration factor into a structured grid, thereby standardizing and improving the calculation process and preventing distorted data.

[0086] The present invention provides a flow field acceleration factor correction method, device, equipment and storage medium based on multi-point short-term wind measurement data, which obtains the flow field acceleration factor of each grid point in the flow field space and the wind measurement data of each sector of the wind measurement point; performs wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain the reconstructed acceleration factor of the flow field reconstruction grid point; performs data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine the reference acceleration factor of each sector of the wind measurement point; and performs correction processing on the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain the target corrected acceleration factor. The method is used to solve the defect of the acceleration factor having errors in the prior art, and realizes that the acceleration factor can be corrected by using multi-point short-term wind measurement data, so as to improve the accuracy of the acceleration factor generation and reduce the errors in the acceleration factor.

[0087] The flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention is described below. The flow field acceleration factor correction device based on multi-point short-term wind measurement data described below and the flow field acceleration factor correction method based on multi-point short-term wind measurement data described above can be referenced to each other.

[0088] like Figure 4 The present invention provides a flow field acceleration factor correction device based on multi-point short-term wind measurement data, which includes the following modules: An acquisition module 410 is used to acquire a flow field acceleration factor of each grid point in the flow field space, and acquire wind measurement data of each sector of the wind measurement point; A reconstruction module 420 is used to perform wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; A determination module 430 is used to perform data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; The correction module 440 is used to correct the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor.

[0089] Optionally, the flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention is specifically used to obtain an initial flow field acceleration factor, and calculate the difference between the reference acceleration factor and the reconstructed acceleration factor to obtain the acceleration factor difference; Determine whether the acceleration factor difference is less than a preset difference threshold; If yes, the initial flow field acceleration factor is used as the target correction acceleration factor; If not, the reference acceleration factor, the reconstruction acceleration factor, and the initial flow field acceleration factor are calculated using the acceleration factor correction formula to obtain a new correction acceleration factor; the new correction acceleration factor is reconstructed to generate a new reconstruction acceleration factor; and the difference between the reference acceleration factor and the new reconstruction acceleration factor is calculated to obtain a new acceleration factor difference; Determine whether the new acceleration factor difference is less than the preset difference threshold; If not, the following steps are executed cyclically: using the acceleration factor correction formula, calculating the reference acceleration factor, the new reconstructed acceleration factor, and the corrected acceleration factor obtained in the previous cycle to obtain a new corrected acceleration factor; reconstructing the new corrected acceleration factor to generate a new reconstructed acceleration factor; calculating the difference between the reference acceleration factor and the new reconstructed acceleration factor to obtain a new acceleration factor difference; and determining whether the new acceleration factor difference is less than the preset difference threshold; If so, the loop is stopped, and the new modified acceleration factor corresponding to the current loop round is used as the target modified acceleration factor.

[0090] Optionally, the flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention is specifically used to perform data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine the reference acceleration factor of each sector of the wind measurement point, including: Preprocessing the wind measurement data of each sector of the wind measurement point to obtain preprocessed wind measurement data; the preprocessed wind measurement data includes wind speed data and wind direction data; The wind speed data and the wind direction data of each sector of the wind measuring point are calculated and processed to obtain a reference acceleration factor of each sector of the wind measuring point.

[0091] Optionally, the flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention is specifically used to pre-process the wind measurement data of each sector of the wind measurement point to obtain pre-processed wind measurement data, including: Performing highly unified calculation processing on the wind measurement data of each sector of the wind measurement point to obtain short-term wind measurement data of a unified height; The short-term wind measurement data at the uniform height are subjected to time interpolation processing to obtain the pre-processed wind measurement data at the same time.

[0092] Optionally, the flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention is also specifically used for the reference acceleration factor including: a first equivalent acceleration factor and a second equivalent acceleration factor; calculating and processing the wind speed data and the wind direction data of each sector of the wind measurement point to obtain a wind speed vector average value; Splitting and calculating the average value of the wind speed vector to obtain a first wind speed vector and a second wind speed vector; The first wind speed vector and the second wind speed vector are subjected to wind speed conversion processing to obtain the first equivalent acceleration factor and the second equivalent acceleration factor.

[0093] Optionally, the flow field acceleration factor correction device based on multi-point short-term wind measurement data provided by the present invention is also specifically used for obtaining the flow field acceleration factor of each grid point in the flow field space, including: Performing flow field modeling processing on the wind farm area to obtain the flow field space of the wind farm area; The flow field acceleration factor of each grid point in each sector is obtained from the flow field space using a data linear interpolation algorithm.

[0094] The present invention provides a flow field acceleration factor correction method, device, equipment and storage medium based on multi-point short-term wind measurement data, which obtains the flow field acceleration factor of each grid point in the flow field space and the wind measurement data of each sector of the wind measurement point; performs wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain the reconstructed acceleration factor of the flow field reconstruction grid point; performs data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine the reference acceleration factor of each sector of the wind measurement point; and performs correction processing on the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain the target corrected acceleration factor. The method is used to solve the defect of the acceleration factor having errors in the prior art, and realizes that the acceleration factor can be corrected by using multi-point short-term wind measurement data, so as to improve the accuracy of the acceleration factor generation and reduce the errors in the acceleration factor.

[0095] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5As shown, the electronic device may include: a processor 510, a communication interface 520, a memory 530 and a communication bus 540, wherein the processor 510, the communication interface 520 and the memory 530 communicate with each other through the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a flow field acceleration factor correction method based on multi-point short-term wind measurement data, the method comprising: obtaining a flow field acceleration factor of each grid point in the flow field space, and obtaining wind measurement data of each sector of the wind measurement point; performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; and performing correction processing on the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target correction acceleration factor.

[0096] In addition, the logic instructions in the above-mentioned memory 530 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0097] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the above methods, the method including: obtaining the flow field acceleration factor of each grid point in the flow field space, and obtaining the wind measurement data of each sector of the wind measurement point; performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor for each sector of the wind measurement point; based on the reference acceleration factor and the reconstructed acceleration factor, correcting the flow field acceleration factor to obtain a target corrected acceleration factor.

[0098] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the flow field acceleration factor correction method based on multi-point short-term wind measurement data provided by the above-mentioned methods, the method comprising: obtaining the flow field acceleration factor of each grid point in the flow field space, and obtaining the wind measurement data of each sector of the wind measurement point; performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor for each sector of the wind measurement point; and performing correction processing on the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor.

[0099] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0100] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for correcting flow field acceleration factor based on multi-point short-term wind measurement data, characterized in that: include: Obtain the flow field acceleration factor of each grid point in the flow field space, and obtain the wind measurement data of each sector of the wind measurement point; Performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; Performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; Based on the reference acceleration factor and the reconstructed acceleration factor, the flow field acceleration factor is corrected to obtain a target corrected acceleration factor.

2. The flow field acceleration factor correction method based on multi-point short-term wind measurement data according to claim 1 is characterized in that: The process of correcting the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor includes: Acquire an initial flow field acceleration factor, and calculate a difference between the reference acceleration factor and the reconstructed acceleration factor to obtain an acceleration factor difference; Determine whether the acceleration factor difference is less than a preset difference threshold; If yes, the initial flow field acceleration factor is used as the target correction acceleration factor; If not, the reference acceleration factor, the reconstruction acceleration factor, and the initial flow field acceleration factor are calculated using the acceleration factor correction formula to obtain a new correction acceleration factor; the new correction acceleration factor is reconstructed to generate a new reconstruction acceleration factor; and the difference between the reference acceleration factor and the new reconstruction acceleration factor is calculated to obtain a new acceleration factor difference; Determine whether the new acceleration factor difference is less than the preset difference threshold; If not, the following steps are executed cyclically: using the acceleration factor correction formula, calculating the reference acceleration factor, the new reconstructed acceleration factor, and the corrected acceleration factor obtained in the previous cycle to obtain a new corrected acceleration factor; reconstructing the new corrected acceleration factor to generate a new reconstructed acceleration factor; calculating the difference between the reference acceleration factor and the new reconstructed acceleration factor to obtain a new acceleration factor difference; and determining whether the new acceleration factor difference is less than the preset difference threshold; If so, the loop is stopped, and the new modified acceleration factor corresponding to the current loop round is used as the target modified acceleration factor.

3. The flow field acceleration factor correction method based on multi-point short-term wind measurement data according to claim 1 is characterized in that: The performing data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine the reference acceleration factor of each sector of the wind measurement point includes: Preprocessing the wind measurement data of each sector of the wind measurement point to obtain preprocessed wind measurement data; the preprocessed wind measurement data includes wind speed data and wind direction data; The wind speed data and the wind direction data of each sector of the wind measuring point are calculated and processed to obtain a reference acceleration factor of each sector of the wind measuring point.

4. The flow field acceleration factor correction method based on multi-point short-term wind measurement data according to claim 3 is characterized in that: The preprocessing of the wind measurement data of each sector of the wind measurement point to obtain preprocessed wind measurement data includes: Performing highly unified calculation processing on the wind measurement data of each sector of the wind measurement point to obtain short-term wind measurement data of a unified height; The short-term wind measurement data at the uniform height are subjected to time interpolation processing to obtain the pre-processed wind measurement data at the same time.

5. The method for correcting flow field acceleration factor based on multi-point short-term wind measurement data according to claim 3 is characterized in that: The reference acceleration factor includes: a first equivalent acceleration factor and a second equivalent acceleration factor; The calculating and processing the wind speed data and the wind direction data of each sector of the wind measuring point to obtain a reference acceleration factor of each sector of the wind measuring point includes: Calculating and processing the wind speed data and the wind direction data of each sector of the wind measuring point to obtain a wind speed vector average value; Splitting and calculating the average value of the wind speed vector to obtain a first wind speed vector and a second wind speed vector; The first wind speed vector and the second wind speed vector are subjected to wind speed conversion processing to obtain the first equivalent acceleration factor and the second equivalent acceleration factor.

6. The flow field acceleration factor correction method based on multi-point short-term wind measurement data according to any one of claims 1 to 5, characterized in that: The step of obtaining the flow field acceleration factor of each grid point in the flow field space includes: Performing flow field modeling processing on the wind farm area to obtain the flow field space of the wind farm area; The flow field acceleration factor of each grid point in each sector is obtained from the flow field space using a data linear interpolation algorithm.

7. A flow field acceleration factor correction device based on multi-point short-term wind measurement data, characterized in that: include: An acquisition module is used to obtain the flow field acceleration factor of each grid point in the flow field space, and to obtain the wind measurement data of each sector of the wind measurement point; A reconstruction module, used for performing wind measurement point sector reconstruction processing on the flow field acceleration factor of each grid point in the flow field space to obtain a reconstructed acceleration factor of the flow field reconstruction grid point; A determination module, used to perform data assimilation processing on the wind measurement data of each sector of the wind measurement point to determine a reference acceleration factor of each sector of the wind measurement point; The correction module is used to correct the flow field acceleration factor based on the reference acceleration factor and the reconstructed acceleration factor to obtain a target corrected acceleration factor.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the flow field acceleration factor correction method based on multi-point short-term wind measurement data as described in any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the flow field acceleration factor correction method based on multi-point short-term wind measurement data as claimed in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the flow field acceleration factor correction method based on multi-point short-term wind measurement data as claimed in any one of claims 1 to 6 is implemented.

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