Wind acceleration factor determination method, device and electronic equipment

Abstract

The present invention provides a method, device, and electronic device for determining a wind acceleration factor, relating to the field of wind power generation technology. The method comprises: obtaining wind measurement data from a wind farm's wind tower; determining the actual wind shear value at the wind farm's wind tower based on the wind measurement data; and determining a simulated wind shear value at the wind tower; iteratively optimizing a wind profile model at the wind farm's inlet boundary based on the actual wind shear value and the simulated wind shear value; and inputting the iteratively optimized wind profile model as an inlet boundary condition into preset simulation software to simulate and calculate the wind acceleration factors at each wind turbine and wind tower in the wind farm. The present invention can establish a wind profile module that adapts to the atmospheric boundary, and the calculated wind acceleration factor is more consistent with the actual conditions of the wind farm, thereby improving the calculation accuracy of the wind acceleration factor.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular to a method, device and electronic equipment for determining a wind acceleration factor. Background Art

[0002] With the development of wind power technology, its application is becoming increasingly widespread in my country. More and more wind power construction companies are realizing that calculating the 50-year maximum wind speed is crucial for assessing the ultimate load of wind turbines and is an important factor in wind turbine selection. To accurately estimate the 50-year maximum wind speed, the wind acceleration factor (WAF) at each turbine site must be calculated. However, existing methods for determining this WAF are primarily based on the simulated wind shear index (WSI) derived from wind farm simulations, resulting in low accuracy. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a method, device and electronic equipment for determining a wind acceleration factor, which can establish a wind profile module adapted to the atmospheric boundary. The calculated wind acceleration factor is more in line with the actual situation of the wind farm, thereby improving the calculation accuracy of the wind acceleration factor.

[0004] In order to achieve the above objectives, the technical solutions adopted in the embodiments of the present invention are as follows:

[0005] In a first aspect, an embodiment of the present invention provides a method for determining a wind acceleration factor, comprising: obtaining wind measurement data from a wind farm wind tower, determining an actual wind shear value at the wind farm wind tower based on the wind measurement data, and determining a simulated wind shear value at the wind tower; iteratively optimizing an inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value; and inputting the iteratively optimized inlet boundary wind profile model as an inlet boundary condition into a preset simulation software to simulate and calculate the wind acceleration factors of each wind turbine in the wind farm and at the wind tower.

[0006] Furthermore, an embodiment of the present invention provides a first possible implementation method of the first aspect, wherein the step of determining the actual wind shear value at the wind farm wind tower based on the wind measurement data includes: determining the representative wind speed corresponding to each height of the wind tower based on the wind measurement data; and determining the actual wind shear value at the wind tower based on the representative wind speed corresponding to each height of the wind tower.

[0007] Furthermore, an embodiment of the present invention provides a second possible implementation of the first aspect, wherein the step of determining the representative wind speed corresponding to each height of the wind measurement tower based on the wind measurement data includes: calculating the completeness rate of the wind measurement data within a preset time period, and judging whether the wind measurement data with a completeness rate greater than the preset completeness rate is qualified; if so, performing data interpolation on the qualified wind measurement data with a completeness rate less than 1 to obtain complete wind measurement data of the wind measurement tower; and performing representative year correction analysis on the complete wind measurement data to obtain the representative wind speed corresponding to each height of the wind measurement tower.

[0008] Furthermore, an embodiment of the present invention provides a third possible implementation method of the first aspect, wherein the step of determining the simulated wind shear value at the wind farm wind tower includes: obtaining the height of the wind tower, the characteristic wind speed at the entrance of the wind farm, and the rough length; determining the simulated wind shear value at the wind tower based on the height of the wind tower, the characteristic wind speed at the entrance of the wind farm, the rough length, and preset simulation software.

[0009] Furthermore, an embodiment of the present invention provides a fourth possible implementation of the first aspect, wherein the step of iteratively optimizing the inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value includes: calculating the shear difference corresponding to the wind tower based on the actual wind shear value and the simulated wind shear value; iteratively correcting the roughness length in the inlet boundary wind profile model of the wind farm until the shear difference is less than a preset value, thereby obtaining the iteratively optimized inlet boundary wind profile model.

[0010] Furthermore, an embodiment of the present invention provides a fifth possible implementation of the first aspect, wherein the shear difference is calculated as follows:

[0011]

[0012] Wherein, ΔQ is the shear difference, Q Met is the actual wind shear value, Q o is the simulated wind shear value.

[0013] Furthermore, an embodiment of the present invention provides a sixth possible implementation of the first aspect, wherein the inlet boundary wind profile model of the wind farm is:

[0014]

[0015] Where U(z) is the wind speed at the height z of the wind tower, K is a constant, z0 is the roughness length, and U * is the characteristic wind speed at the entrance of the wind farm.

[0016] In the second aspect, an embodiment of the present invention also provides a device for determining a wind acceleration factor, including a first determination module for obtaining wind measurement data from a wind farm wind tower, determining the actual wind shear value at the wind farm wind tower based on the wind measurement data, and determining the simulated wind shear value at the wind tower; a second determination module for iteratively optimizing the inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value; and a calculation module for inputting the iteratively optimized inlet boundary wind profile model as an inlet boundary condition into a preset simulation software to simulate and calculate the wind acceleration factors of each wind turbine and wind tower in the wind farm.

[0017] In a third aspect, an embodiment of the present invention provides an electronic device comprising: a processor and a storage device; the storage device stores a computer program, and when the computer program is executed by the processor, it executes the method as described in any one of the first aspects.

[0018] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in any one of the above-mentioned first aspects are executed.

[0019] An embodiment of the present invention provides a method, device and electronic device for determining a wind acceleration factor. The method for determining a wind acceleration factor includes: obtaining wind measurement data from a wind tower in a wind farm, determining an actual wind shear value at the wind tower in the wind farm based on the wind measurement data, and determining a simulated wind shear value at the wind tower; iteratively optimizing an inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value; and inputting the iteratively optimized inlet boundary wind profile model as an inlet boundary condition into preset simulation software to simulate and calculate the wind acceleration factors of each wind turbine in the wind farm and at the wind tower.

[0020] The wind acceleration factor determination method provided by the present invention calculates the actual wind shear value at the wind farm wind tower based on the actual wind measurement data of the wind farm wind tower, and repeatedly iteratively optimizes the wind profile model at the wind farm entrance boundary based on the difference between the actual wind shear value and the simulated wind shear value. This can establish a wind profile module that is adapted to the atmospheric boundary, and the calculated wind acceleration factor is more in line with the actual situation of the wind farm, thereby improving the calculation accuracy and rationality of the wind acceleration factor.

[0021] Other features and advantages of the embodiments of the present invention will be described in the following description, or some features and advantages can be inferred or determined without doubt from the description, or can be learned by implementing the above-mentioned technologies of the embodiments of the present invention.

[0022] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific 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 any creative work.

[0024] Figure 1 A flow chart of a method for determining a wind acceleration factor provided by an embodiment of the present invention is shown;

[0025] Figure 2 A schematic structural diagram of a device for determining a wind acceleration factor provided by an embodiment of the present invention is shown;

[0026] Figure 3 A schematic structural diagram of an electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0028] This embodiment provides a method for determining a wind acceleration factor, which is applied to electronic devices such as computers. Figure 1 The flow chart of the method for determining the wind acceleration factor is shown in FIG. 1 , and the method for determining the wind acceleration factor mainly includes the following steps:

[0029] Step S102 : obtaining wind measurement data from a wind farm wind tower, determining an actual wind shear value at the wind farm wind tower based on the wind measurement data, and determining a simulated wind shear value at the wind tower.

[0030] The above-mentioned wind acceleration factor is the wind acceleration factor for each machine site in the wind farm. The wind acceleration factor for each machine site is the ratio of the wind speed at each machine site to the incoming wind speed. The wind tower of the wind farm detects wind data (including wind speed and wind direction data) once every certain interval (such as 5 to 10 minutes). Based on all wind data of the wind farm within a preset period (such as one year), the wind shear value at the wind tower is determined and recorded as the actual wind shear value. The characteristic wind speed and roughness length at the entrance of the wind farm are obtained, and the wind shear value of the wind tower is simulated and calculated based on the characteristic wind speed and roughness length at the entrance of the wind farm, and recorded as the simulated wind shear value.

[0031] Step S104 : iteratively optimizing the inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value.

[0032] According to the difference between the actual wind shear value and the simulated wind shear value, the inlet boundary wind profile model is iteratively optimized to correct the wind profile at the inlet boundary of the wind farm so that the difference between the actual wind shear value and the simulated wind shear value is as small as possible. The inlet boundary wind profile model corresponding to the smaller difference between the actual wind shear value and the simulated wind shear value is obtained.

[0033] Step S106 , inputting the iteratively optimized inlet boundary wind profile model as an inlet boundary condition into a preset simulation software to simulate and calculate the wind acceleration factor of each wind turbine in the wind farm and at the wind tower.

[0034] The above-mentioned preset simulation software can be computer software capable of performing wind farm simulation calculations, such as OpenFOAM. The iteratively optimized inlet boundary wind profile model is input into OpenFOAM as the inlet boundary condition, and the wind acceleration factor at each machine site is simulated and calculated using OpenFOAM.

[0035] When OpenFOAM simulates and extrapolates the wind acceleration factor at each turbine site, it numerically discretizes the established NS control equation based on the inlet boundary wind profile model as the boundary condition to solve the wind speed at each turbine site, and solves the wind acceleration factor at each turbine site based on the wind speed at each turbine site and the incoming wind speed (including the wind acceleration factor at each wind turbine and wind tower. The wind acceleration factor at each turbine site is the ratio of the wind speed at each turbine site to the incoming wind speed). The above NS control equation is:

[0036]

[0037] Where ρ is the air density at each machine point, t is time, U is the wind speed at each machine point, and τ is the stress at each machine point. To calculate the gradient, To calculate the divergence.

[0038] The above-mentioned method for determining the wind acceleration factor provided in this embodiment calculates the actual wind shear value at the wind farm wind tower based on the actual wind measurement data of the wind farm wind tower, and repeatedly iteratively optimizes the wind profile model at the wind farm entrance boundary based on the difference between the actual wind shear value and the simulated wind shear value. This can establish a wind profile module that is adapted to the atmospheric boundary. The calculated wind acceleration factor is more consistent with the actual situation of the wind farm, thereby improving the calculation accuracy of the wind acceleration factor.

[0039] In a feasible implementation, this embodiment provides an implementation for determining the actual wind shear value at a wind farm wind tower based on wind measurement data, which can be specifically performed with reference to the following steps (1) to (2):

[0040] Step (1): Determine the representative wind speed corresponding to each height of the wind tower based on the wind measurement data.

[0041] Calculate the completeness rate of wind measurement data within a preset time period and determine whether wind measurement data with a completeness rate greater than the preset completeness rate is qualified. Obtain the actual number of wind measurement data collected by the wind tower in a year. Based on the wind measurement data collection frequency of the wind tower, determine the total number of wind measurement data that the wind tower should collect in a year. For example, if the wind tower collects wind measurement data every 10 minutes, the total number of wind measurement data = (24 hours / 10 minutes) * 365.

[0042] The completeness rate of wind measurement data is calculated as: actual number of wind measurement data / total number of wind measurement data. When the completeness rate of wind measurement data is greater than 90%, the wind measurement data of the wind measurement tower is determined to be valid, and the rationality of the valid wind measurement data is further determined.

[0043] Obtain hourly average wind speed, average wind direction, and average air pressure from the tower's valid wind data. When 0 ≤ average wind speed ≤ 40 m / s, 0° ≤ average wind direction ≤ 306°, and 94 kPa ≤ average air pressure ≤ 106 kPa, determine whether the change in average wind speed within 1 hour is < 6 m / s, the change in average temperature within 1 hour is < 5°, and the change in average air pressure within 1 hour is < 1 kPa. If all of these conditions are met, the wind data is considered reasonable. If any wind data does not meet these conditions, determine the detection time for unreasonable wind data and eliminate the unreasonable wind data. When the wind data from the tower meets the above requirements for completeness and rationality, the tower's wind data is considered qualified.

[0044] If so, data interpolation is performed on qualified wind measurement data with a completeness rate less than 1 to obtain complete wind measurement data from the wind measurement tower. Since there may still be missing data when the wind measurement data of a wind measurement tower is qualified, data interpolation is performed on the wind measurement data with missing data. The correlation between the wind measurement data with missing data and the wind measurement data of other wind measurement towers is calculated based on the least squares method. Data interpolation is performed based on the wind measurement data of the wind measurement tower with the greatest correlation. That is, the wind measurement data at the corresponding time and height of the wind measurement tower with the greatest correlation is interpolated to the missing data location.

[0045] A representative year correction analysis was performed on the complete wind measurement data to obtain the representative wind speed corresponding to each tower height. The interpolated wind measurement data was recorded as the complete wind measurement data. Wind measurement data from the meteorological station where the wind farm is located was obtained and a representative year correction analysis was performed on the complete wind measurement data based on the correction formula: average wind speed at the meteorological station for the current year / average wind speed at the meteorological station over the past 20 years = current average wind speed at the tower / representative wind speed at the tower for the current year.

[0046] Based on the representative wind speed of the wind tower in that year and the sector where each wind measurement data is located, each wind measurement data of the wind tower in that year is corrected. The correction principle is the same as that of the above correction formula, and the representative wind speed corresponding to each height of the wind tower is obtained.

[0047] Step (2): Determine the actual wind shear value at the wind tower based on the representative wind speed corresponding to each height of the wind tower.

[0048] The actual wind shear value at the wind tower is calculated based on the representative wind speed at each height of the wind tower. The actual wind shear value includes the shear value at each height of the wind tower. The wind shear value calculation formula is:

[0049] Where Q is the wind shear value, U(z2) is the wind speed at the z2 height of the wind tower, and U(z1) is the wind speed at the z1 height of the wind tower. Input the representative wind speeds at each tower height into the wind shear value calculation formula to obtain the actual wind shear value at the tower. See Table 1 below for the actual wind shear value table for a particular tower. Table 1 shows the actual wind shear index at various tower heights. For example, the wind shear value at 180 meters from a tower 120 meters tall is 0.178:

[0050] Table 1 Actual shear value of wind tower

[0051] Side layer 180m 160m 140m 120m 100m 80m 60m 40m 180m 0.179 0.177 0.178 0.181 0.181 0.183 0.188 160m 0.179 0.181 0.184 0.183 0.185 0.190 140m 0.186 0.188 0.185 0.186 0.192 120m 0.191 0.185 0.186 0.194 100m 0.182 0.186 0.196 80m 0.190 0.200 60m 0.207

[0052] In one feasible implementation, this embodiment provides an approach for determining a simulated wind shear value at a wind farm's wind tower: obtaining the tower's height, the characteristic wind speed at the wind farm entrance, and the roughness length; and determining the simulated wind shear value at the tower based on the tower's height, the characteristic wind speed at the wind farm entrance, the roughness length, and preset simulation software. The tower's height, the characteristic wind speed at the wind farm entrance, and the roughness length are input into OpenFOAM software for sector simulation calculation to simulate wind speeds at various tower heights. The wind speeds at various tower heights are then input into the aforementioned wind shear value calculation formula to obtain the wind shear value at the tower, which is recorded as the simulated wind shear value.

[0053] In a feasible implementation, this embodiment provides an implementation for iteratively optimizing the inlet boundary wind profile model of a wind farm based on actual wind shear values ​​and simulated wind shear values. Specifically, the optimization can be performed with reference to the following steps 1) to 2):

[0054] Step 1): Calculate the shear difference corresponding to the wind tower based on the actual wind shear value and the simulated wind shear value.

[0055] The calculation formula for the shear difference between the actual wind shear value and the simulated wind shear value is:

[0056]

[0057] Where ΔQ is the shear difference, Q Metis the actual wind shear value, Q o is the simulated wind shear value.

[0058] Step 2): iteratively modify the roughness length in the inlet boundary wind profile model of the wind farm until the shear difference is less than a preset value, thereby obtaining an iteratively optimized inlet boundary wind profile model.

[0059] The inlet boundary wind profile model of the above wind farm is:

[0060]

[0061] Where U(z) is the wind speed at the height z of the wind tower, K is a constant, z0 is the roughness length, and U * is the characteristic wind speed at the wind farm inlet. The roughness length in the inlet boundary wind profile model is repeatedly iteratively corrected. As the roughness length changes, the wind speed at each corresponding tower height also changes, leading to changes in the calculated wind shear value and shear difference. By iteratively correcting the roughness length, the calculated shear difference is kept within a preset value (such as ΔQ < 1%), which can be between 1% and 0.5%, resulting in an inlet boundary condition consistent with the tower shear index.

[0062] The wind acceleration factor determination method provided in this embodiment accurately calculates the wind acceleration factor at each aircraft location by simulating time series data at the wind tower coordinates using OpenFOAM. By comparing the simulated wind shear at the wind tower coordinates with the actual wind shear, the wind profile model at the inlet boundary is repeatedly optimized. This provides an accurate basis for calculating the 50-year maximum wind speed at each aircraft location.

[0063] In a feasible implementation, this embodiment provides an example of inputting the height of the wind tower, the characteristic wind speed at the wind farm entrance, and the roughness length into the OpenFOAM simulation software to calculate the wind speed at various heights of the wind tower and wind turbines:

[0064]

[0065]

[0066] By inputting the wind speed at each height of the wind tower obtained by OpenFOAM simulation into the above wind shear value calculation formula, the corresponding shear value at each height of the wind tower can be obtained.

[0067] Corresponding to the wind acceleration factor determination method provided in the above embodiment, the embodiment of the present invention provides a wind acceleration factor determination device, see Figure 2 The structure diagram of a device for determining a wind acceleration factor is shown, and the device includes the following modules:

[0068] The first determination module 21 is configured to obtain wind measurement data from a wind farm wind tower, determine an actual wind shear value at the wind farm wind tower based on the wind measurement data, and determine a simulated wind shear value at the wind tower.

[0069] The second determining module 22 is configured to iteratively optimize the inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value.

[0070] The calculation module 23 is used to input the iteratively optimized inlet boundary wind profile model as the inlet boundary condition into the preset simulation software to simulate and calculate the wind acceleration factor of each wind turbine in the wind farm and the wind tower.

[0071] The wind acceleration factor determination device provided in this embodiment calculates the actual wind shear value at the wind farm tower based on the actual wind measurement data of the wind farm tower, and repeatedly iteratively optimizes the wind profile model at the wind farm entrance boundary based on the difference between the actual wind shear value and the simulated wind shear value. This can establish a wind profile module that is adapted to the atmospheric boundary, and the calculated wind acceleration factor is more consistent with the actual situation of the wind farm, thereby improving the calculation accuracy of the wind acceleration factor.

[0072] In one embodiment, the first determining module 21 is further configured to determine representative wind speeds corresponding to each height of the wind tower based on the wind measurement data; and determine actual wind shear values ​​at the wind tower based on the representative wind speeds corresponding to each height of the wind tower.

[0073] In one embodiment, the first determination module 21 is further used to calculate the completeness rate of wind measurement data within a preset time period, and determine whether the wind measurement data with a completeness rate greater than the preset completeness rate is qualified; if so, data interpolation is performed on the qualified wind measurement data with a completeness rate less than 1 to obtain complete wind measurement data of the wind measurement tower; and representative year correction analysis is performed on the complete wind measurement data to obtain representative wind speeds corresponding to each height of the wind measurement tower.

[0074] In one embodiment, the first determination module 21 is further used to obtain the height of the wind tower, the characteristic wind speed at the entrance of the wind farm, and the roughness length; and determine the simulated wind shear value at the wind tower based on the height of the wind tower, the characteristic wind speed at the entrance of the wind farm, the roughness length, and the preset simulation software.

[0075] In one embodiment, the second determination module 22 is further used to calculate the shear difference corresponding to the wind tower based on the actual wind shear value and the simulated wind shear value; iteratively correct the roughness length in the inlet boundary wind profile model of the wind farm until the shear difference is less than a preset value, thereby obtaining an iteratively optimized inlet boundary wind profile model.

[0076] In one embodiment, the shear difference is calculated as follows:

[0077]

[0078] Where ΔQ is the shear difference, Q Met is the actual wind shear value, Q o is the simulated wind shear value.

[0079] In one embodiment, the inlet boundary wind profile model of the wind farm is:

[0080]

[0081] Where U(z) is the wind speed at the height z of the wind tower, K is a constant, z0 is the roughness length, and U * is the characteristic wind speed at the entrance of the wind farm.

[0082] The wind acceleration factor determination device provided in this embodiment accurately calculates the wind acceleration factor at each aircraft location by simulating time series data at the wind tower coordinates based on OpenFOAM. By comparing the simulated wind shear at the wind tower coordinates with the actual wind shear, the wind profile model at the inlet boundary is repeatedly optimized. This provides an accurate basis for calculating the 50-year maximum wind speed at each aircraft location.

[0083] The device provided in this embodiment has the same implementation principle and technical effects as those of the aforementioned embodiments. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment.

[0084] An embodiment of the present invention provides an electronic device, such as Figure 3 As shown in the structural diagram of the electronic device, the electronic device includes a processor 31 and a memory 32. The memory stores a computer program that can be run on the processor. When the processor executes the computer program, the steps of the method provided in the above embodiment are implemented.

[0085] See also Figure 3 The electronic device further includes a bus 34 and a communication interface 33. The processor 31, the communication interface 33 and the memory 32 are connected via the bus 34. The processor 31 is configured to execute executable modules stored in the memory 32, such as computer programs.

[0086] The memory 32 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage. The system network element communicates with at least one other network element via at least one communication interface 33 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0087] The bus 34 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 3 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0088] Among them, the memory 32 is used to store programs, and the processor 31 executes the program after receiving the execution instruction. The method executed by the device for flow process definition disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 31 or implemented by the processor 31.

[0089] The processor 31 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in the processor 31 or by software instructions. The processor 31 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc. It may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in conjunction with the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in memory 32, and processor 31 reads information in memory 32 and, in conjunction with its hardware, completes the steps of the above method.

[0090] An embodiment of the present invention provides a computer-readable medium, wherein the computer-readable medium stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the method described in the above embodiment.

[0091] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the system described above can refer to the corresponding process in the aforementioned embodiment and will not be repeated here.

[0092] The computer program product of the wind acceleration factor determination method, device and electronic device provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiments. The specific implementation can be found in the method embodiments and will not be repeated here.

[0093] In addition, in the description of the embodiments of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0094] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, 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. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0095] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0096] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for determining a wind acceleration factor, characterized in that: include: Acquire wind measurement data from a wind farm wind tower, determine an actual wind shear value at the wind farm wind tower based on the wind measurement data, and determine a simulated wind shear value at the wind tower; Iteratively optimizing an inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value; The iteratively optimized inlet boundary wind profile model is input as the inlet boundary condition into a preset simulation software to simulate and calculate the wind acceleration factor of each wind turbine and wind tower in the wind farm; wherein the preset simulation software is wind farm simulation software; The step of determining the actual wind shear value at the wind farm wind tower based on the wind measurement data comprises: Calculating the integrity rate of the wind measurement data within a preset time period, and determining whether the wind measurement data having the integrity rate greater than the preset integrity rate is qualified; If yes, perform data interpolation on the qualified wind measurement data with a completeness rate less than 1 to obtain complete wind measurement data of the wind measurement tower; Performing a representative year correction analysis on the complete wind measurement data to obtain representative wind speeds corresponding to each height of the wind measurement tower; wherein the representative year correction analysis on the complete wind measurement data is performed based on a correction formula, and the correction formula is: average wind speed of the weather station in that year / average wind speed of the weather station in the past 20 years = current average wind speed of the wind measurement tower / representative wind speed of the wind measurement tower in that year; Determining an actual wind shear value at the wind tower based on representative wind speeds corresponding to each height of the wind tower; The step of determining the simulated wind shear value at the wind farm wind tower includes: Obtaining the height of the wind tower, the characteristic wind speed at the entrance of the wind farm, and the roughness length; The simulated wind shear value at the wind tower is determined based on the height of the wind tower, the characteristic wind speed at the entrance of the wind farm, the roughness length, and preset simulation software.

2. The method according to claim 1, characterized in that The step of iteratively optimizing the inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value comprises: Calculating a shear difference corresponding to the wind tower based on the actual wind shear value and the simulated wind shear value; The roughness length in the inlet boundary wind profile model of the wind farm is iteratively corrected until the shear difference is less than a preset value, thereby obtaining an iteratively optimized inlet boundary wind profile model.

3. The method according to claim 2, characterized in that The calculation formula of the shear difference is: Wherein, ΔQ is the shear difference, Q Met is the actual wind shear value, Q o is the simulated wind shear value.

4. The method according to claim 2, characterized in that The wind profile model of the inlet boundary of the wind farm is: Where U(z) is the wind speed at the height z of the wind tower, K is a constant, z0 is the roughness length, and U * is the characteristic wind speed at the entrance of the wind farm.

5. A device for determining a wind acceleration factor, characterized in that: A first determination module is configured to obtain wind measurement data from a wind farm wind tower, determine an actual wind shear value at the wind farm wind tower based on the wind measurement data, and determine a simulated wind shear value at the wind tower; a second determining module, configured to iteratively optimize an inlet boundary wind profile model of the wind farm based on the actual wind shear value and the simulated wind shear value; a calculation module, configured to input the iteratively optimized inlet boundary wind profile model as an inlet boundary condition into a preset simulation software to simulate and calculate the wind acceleration factor of each wind turbine and wind tower in the wind farm; wherein the preset simulation software is wind farm simulation software; The first determination module is used to calculate the completeness rate of the wind measurement data within a preset time period, and determine whether the wind measurement data with a completeness rate greater than the preset completeness rate is qualified; if so, perform data interpolation on the qualified wind measurement data with a completeness rate less than 1 to obtain complete wind measurement data of the wind measurement tower; perform representative year correction analysis on the complete wind measurement data to obtain representative wind speeds corresponding to each height of the wind measurement tower; determine the actual wind shear value at the wind measurement tower based on the representative wind speeds corresponding to each height of the wind measurement tower; wherein, the representative year correction analysis of the complete wind measurement data is performed based on a formula, and the correction formula is: average wind speed of the weather station in the current year / average wind speed of the weather station in the past 20 years = current average wind speed of the wind measurement tower / representative wind speed of the wind measurement tower in the current year; The first determination module is used to obtain the height of the wind measurement tower, the characteristic wind speed at the entrance of the wind farm, and the rough length; and determine the simulated wind shear value at the wind measurement tower based on the height of the wind measurement tower, the characteristic wind speed at the entrance of the wind farm, the rough length, and preset simulation software.

6. An electronic device, characterized in that: include: processors and storage devices; The storage device stores a computer program, which, when executed by the processor, executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are executed.

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