Turbulence intensity determination method and device, electronic equipment and storage medium

Abstract

The invention discloses a turbulence intensity determination method and device, electronic equipment and a storage medium. The method comprises the following steps: generating a turbulence matrix according to wind speed data, wind direction data and measured turbulence intensity; eliminating the measurement turbulence intensity corresponding to the wind speed section which does not meet the measurement target in the turbulence matrix, and determining the wind speed section after eliminating the measurement turbulence intensity as a target wind speed section; for each target wind speed section, fitting a plurality of wind speed sections in a target sector corresponding to the target wind speed section with the measured turbulence intensity corresponding to each wind speed section to obtain a target fitting function, and determining a target correlation coefficient of the target fitting function and the measured turbulence intensity; and determining the target turbulence intensity according to the target correlation coefficient. According to the scheme of the invention, the turbulence intensity of the wind speed section with abnormal measurement is determined, the accuracy of turbulence intensity determination is improved, and the accuracy of wind resource assessment in the wind power plant is enhanced.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation, and in particular to a method, device, electronic device and storage medium for determining turbulence intensity. Background Art

[0002] As energy and environmental issues become increasingly prominent, wind energy as a clean, renewable energy source is gaining more and more attention, and more and more wind farms are located in more complex mountainous areas. In complex mountainous areas, the environmental turbulence intensity of wind farm distribution is also more complex.

[0003] At present, the ambient turbulence intensity of the wind field distribution (abbreviated as turbulence intensity) is calculated using the computational fluid dynamics (CFD) method and then corrected according to the actual measured wind speed and wind direction.

[0004] However, due to the complex environment of wind farms, wind direction and wind speed measurements in wind farms often result in fewer measurement samples or missing measurement data, which requires the measurement data to be filled in based on human experience when determining the turbulence intensity. This results in low accuracy of the turbulence intensity, which in turn affects the assessment of wind resources in wind farms and, in turn, the siting results of wind turbines. Summary of the invention

[0005] The present application provides a turbulence intensity determination method, device, electronic device and storage medium to solve the problem in the prior art that due to the complex wind farm environment, the wind direction and wind speed measurements in the wind farm often have a small number of measurement samples or missing measurement data, so that when determining the turbulence intensity, it is necessary to fill in the measurement data based on human experience, resulting in low accuracy of the obtained turbulence intensity, which affects the assessment of wind resources in the wind farm and further affects the site selection results of the wind turbine.

[0006] In a first aspect, the present application provides a method for determining turbulence intensity, the method comprising:

[0007] Acquire wind speed data, wind direction data and measured turbulence intensity in the wind farm, and generate a turbulence matrix according to the wind speed data, the wind direction data and the measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensity corresponding to multiple wind speed segments of each wind direction sector in multiple wind direction sectors;

[0008] Eliminating the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determining the wind speed segment after eliminating the measured turbulence intensity as the target wind speed segment;

[0009] For each of the target wind speed segments, multiple wind speed segments in a target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each of the wind speed segments to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined;

[0010] If the target correlation coefficient is less than the preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix;

[0011] If the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function.

[0012] In a second aspect, the present application provides a turbulence intensity determination device, the device comprising:

[0013] An acquisition module is used to acquire wind speed data, wind direction data and measured turbulence intensity in a wind farm, and generate a turbulence matrix according to the wind speed data, the wind direction data and the measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensity corresponding to multiple wind speed segments of each wind direction sector in multiple wind direction sectors;

[0014] A removal module, used to remove the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determine the wind speed segment after removing the measured turbulence intensity as the target wind speed segment;

[0015] A coefficient determination module is used to fit, for each target wind speed segment, a plurality of wind speed segments in a target sector corresponding to the target wind speed segment with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and determine a target correlation coefficient between the target fitting function and the measured turbulence intensity;

[0016] A first determination module, configured to determine the measured turbulence intensity of the adjacent wind speed segment as the target turbulence intensity corresponding to the target wind speed segment if the target correlation coefficient is less than a preset correlation coefficient; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix;

[0017] The second determination module is used to determine the target turbulence intensity corresponding to the target wind speed segment according to the target fitting function if the target correlation coefficient is greater than or equal to the preset correlation coefficient.

[0018] In a third aspect, the present application 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, the method for determining turbulence intensity as described in any embodiment of the present application is implemented.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining turbulence intensity as described in any embodiment of the present application.

[0020] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the turbulence intensity determination method as described in any embodiment of the present application.

[0021] The solution of the present application obtains wind speed data, wind direction data and measured turbulence intensity in a wind farm, and generates a turbulence matrix based on the wind speed data, wind direction data and measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensities corresponding to multiple wind speed segments in each wind direction sector in multiple wind direction sectors; the measured turbulence intensities corresponding to the wind speed segments that do not meet the measurement target in the turbulence matrix are eliminated, and the wind speed segments after the measured turbulence intensity is eliminated are determined as target wind speed segments; for each target wind speed segment, multiple wind speed segments in a target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined; if the target correlation coefficient is less than a preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix; if the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function. That is, the solution of the present application, when the wind direction and wind speed measurements in a wind farm do not meet the measurement targets, determines the corresponding output mode for the turbulence intensity based on the target correlation coefficient, thereby determining the turbulence intensity of the wind speed segment where the measurement abnormality occurs, thereby improving the accuracy of the turbulence intensity determination, thereby enhancing the accuracy of the wind resource assessment in the wind farm and improving the suitability of the site selection for the wind turbines. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solution of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0023] Figure 1is a flow chart of the method for determining turbulence intensity provided in this application;

[0024] Figure 2 is another schematic flow chart of the method for determining turbulence intensity provided in the present application;

[0025] Figure 3 is a structural schematic diagram of a turbulence intensity determination device provided in the present application;

[0026] Figure 4 It is a structural schematic diagram of the electronic device provided by this application. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0028] Figure 1 The present invention provides a flow chart of a method for determining turbulence intensity. The method can be performed by a turbulence intensity determination device, which can be implemented in software and / or hardware. In a specific embodiment, the device can be applied to an electronic device, which can be a computer. The following embodiments will be described by taking the application of the device in an electronic device as an example. Figure 1 , the method may specifically include the following steps:

[0029] Step 101: Obtain wind speed data, wind direction data and measured turbulence intensity in the wind farm, and generate a turbulence matrix according to the wind speed data, wind direction data and measured turbulence intensity.

[0030] The turbulence matrix is ​​used to characterize the measured turbulence intensity corresponding to multiple wind speed segments in each wind direction sector in multiple wind direction sectors.

[0031] Specifically, the wind speed data in the wind farm is the wind speed that may occur in the wind farm, and the wind direction data is the wind direction that may occur in the wind farm. Turbulence intensity refers to the magnitude of the random change in wind speed within 10 minutes, which is the ratio of the standard deviation of the average wind speed in 10 minutes to the average wind speed in the same period. It is the normal fatigue load that the wind turbine withstands during operation and is crucial to the safety of the wind turbine. Measuring turbulence intensity refers to taking statistical parameters of multiple initial measured turbulence intensities at a certain wind speed in a certain wind direction after detecting multiple initial measured turbulence intensities, such as taking the average of multiple initial measured turbulence intensities to obtain the measured turbulence intensity. According to the measured turbulence intensity at each wind speed in each wind direction, a turbulence matrix is ​​generated. For example, the rows of the matrix represent the wind speed and the columns represent the wind direction. The measured turbulence intensity at each wind speed in each wind direction is filled in to obtain the turbulence matrix.

[0032] Step 102: remove the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determine the wind speed segment after removing the measured turbulence intensity as the target wind speed segment.

[0033] Specifically, the measurement target is the detection target that the detected turbulence intensity should reach, so as to ensure the accuracy of the measurement data. For example, the measurement target can be that the number of initial measured turbulence intensities detected is greater than 10. The measured turbulence intensities corresponding to the wind speed segments that do not meet the measurement target in the turbulence matrix are eliminated, that is, the data that may be inaccurately measured are eliminated, and the wind speed segment after eliminating the measured turbulence intensity is determined as the target wind speed segment.

[0034] Exemplarily, the measurement target is that the number of initial measured turbulence intensities corresponding to the wind speed segment is greater than or equal to 10. For the B wind speed segment in the A wind direction, the number of initial measured turbulence intensities detected is 2, and the number of measurement samples is less than 10, which does not meet the measurement requirements. At this time, the measured turbulence intensity corresponding to the B wind speed segment in the A wind direction is eliminated, and the B wind speed segment in the A wind direction after eliminating the measured turbulence intensity is determined as the target wind speed segment.

[0035] Optionally, the measurement target includes that the number of initial measured turbulence intensities corresponding to the wind speed segment is greater than or equal to a preset number.

[0036] Specifically, the initial measured turbulence intensity is the turbulence intensity directly obtained through measurement and calculation. When the number of samples obtained by measurement is sufficient, the measured turbulence intensity is obtained by calculating statistical parameters from multiple initial measured turbulence intensities. Since the turbulence intensity calculated based on the meteorological data actually measured at the wind tower may have missing measurement data or too few samples due to factors such as the wind farm environment and climate, the measured turbulence intensity obtained based on the initial measured turbulence intensity may be inaccurate due to insufficient measurement data. Therefore, the measured turbulence intensity with a number of initial measured turbulence intensities greater than or equal to a preset number is determined as the turbulence intensity that meets the measurement target. For example, the preset number may be 20.

[0037] Optionally, the initial measured turbulence intensity is obtained according to the turbulence intensity actually measured at the wind tower, the directional turbulence intensity calculated at the wind tower, the directional turbulence intensity calculated at the result point, the directional wind acceleration factor calculated at the wind tower, and the directional wind acceleration factor calculated at the result point.

[0038] The directional turbulence intensity calculated at the result point is determined based on the ambient turbulence intensity and the additional turbulence intensity at the result point.

[0039] Specifically, the initial measured turbulence intensity can be obtained by formula 1. The turbulence intensity actually measured at the wind tower is the turbulence intensity actually detected at the wind tower, and the directional turbulence intensity calculated at the wind tower is the turbulence intensity at the location of the wind tower obtained by CFD directional calculation. The result point refers to the specific location of the wind power equipment after the establishment of the wind farm. The directional turbulence intensity calculated at the result point is the turbulence intensity at the location of the result point obtained by CFD directional calculation after considering the wake effect. The directional wind acceleration factor calculated at the wind tower is the directional wind acceleration factor at the location of the wind tower obtained by CFD directional calculation, and the directional wind acceleration factor calculated at the result point is the directional wind acceleration factor at the location of the result point obtained by CFD directional calculation.

[0040] I corp (bin,dir) = I IEC + [I mes (bin,dir)–I calcm (dir)] C m (dir) / C p (dir) Formula 1

[0041] Among them, I corp (bin,dir) is the initial measured turbulence intensity, I mes (bin,dir) is the turbulence intensity actually measured at the wind tower, I calcm(dir) is the directional turbulence intensity calculated at the wind tower, I IEC is the directional turbulence intensity calculated at the result point, C m (dir) is the directional wind acceleration factor calculated at the wind tower, C p (dir) is the directional wind acceleration factor calculated at the result point.

[0042] The directional turbulence intensity calculated at the result point can be obtained by formula 2.

[0043]

[0044] Among them, I IEC is the directional turbulence intensity calculated at the result point, I amb is the ambient turbulence intensity, I add is the additional turbulence intensity. The ambient turbulence intensity is the turbulence intensity obtained by CFD directional calculation. The additional turbulence intensity is the increase in turbulence due to the wake effect. Therefore, the directional turbulence intensity calculated at the result point is the turbulence intensity obtained after adding the influence of the wake effect on the change of the ambient turbulence intensity to the ambient turbulence intensity.

[0045] Step 103, for each target wind speed segment, multiple wind speed segments in the target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and determine a target correlation coefficient between the target fitting function and the measured turbulence intensity.

[0046] Specifically, for each target wind speed segment, multiple wind speed segments in the target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function. The target fitting function may be a power function. The fitting process may be implemented by fitting the data to Formula 3.

[0047] Ti=a*X b Formula 3

[0048] Among them, Ti is the turbulence intensity, X is the wind speed segment corresponding to the turbulence intensity, and a and b are the parameters after the power function fitting. After obtaining the target fitting function, the target correlation coefficient between the target fitting function and the measured turbulence intensity is determined according to the correlation between the target fitting function and the measured turbulence intensity.

[0049] Optionally, determining a target correlation coefficient between a target fitting function and a measured turbulence intensity may be achieved through steps 31 and 32 .

[0050] Step 31, establishing a measurement curve according to a plurality of wind speed segments and the measured turbulence intensity corresponding to each wind speed segment.

[0051] Specifically, a measurement curve is established according to a plurality of wind speed segments and the measured turbulence intensity corresponding to each wind speed segment, that is, discrete measurement values ​​are connected to obtain the measurement curve.

[0052] Step 32, determining a target correlation coefficient between the target fitting function and the measured turbulence intensity according to the degree of correlation between the target fitting function and the measurement curve.

[0053] Specifically, according to the correlation degree between the target fitting function and the measurement curve, that is, the correlation between the two, the target correlation coefficient between the target fitting function and the measured turbulence intensity is determined.

[0054] Step 104: If the target correlation coefficient is less than the preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment.

[0055] Among them, the adjacent wind speed segment is the wind speed segment adjacent to the target wind speed segment in the turbulence matrix.

[0056] Specifically, the preset correlation coefficient is a preset coefficient that can determine that the correlation between the fitting function and the measured value is high enough, so as to determine that the accuracy of the fitted data meets the requirements of data acquisition. If the target correlation coefficient is less than the preset correlation coefficient, it is proved that the measured turbulence data obtained according to the target fitting function is inaccurate. Therefore, at this time, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment.

[0057] Optionally, step 104 may be implemented through steps 41 to 43 .

[0058] Step 41: If the target correlation coefficient is less than the preset correlation coefficient and the adjacent wind speed segment corresponds to a measured turbulence intensity, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment.

[0059] Specifically, if the target correlation coefficient is less than the preset correlation coefficient and the adjacent wind speed segment corresponds to a measured turbulence intensity, that is, the adjacent wind speed segment of the target wind speed segment has measurement data that meets the measurement requirements, then the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment.

[0060] Step 42: If the target correlation coefficient is less than the preset correlation coefficient and there is no corresponding measured turbulence intensity in the adjacent wind speed segment, then determine the adjacent sectors of the target sector corresponding to the target wind speed segment.

[0061] Among them, the adjacent sector is the sector adjacent to the target sector in the turbulence matrix.

[0062] Specifically, if the target correlation coefficient is less than the preset correlation coefficient and there is no corresponding measured turbulence intensity in the adjacent wind speed segment, the adjacent sectors of the sector where the target wind speed segment is located are determined as the adjacent sectors of the target sector corresponding to the target wind speed segment.

[0063] Step 43: determine the target turbulence intensity corresponding to the same wind speed segment of the adjacent sectors as the target turbulence intensity corresponding to the target wind speed segment.

[0064] Among them, the wind speed range of the same wind speed segment is the same as that of the target wind speed segment.

[0065] Specifically, in adjacent sectors, there is a wind speed segment with the same wind speed interval as the target wind speed segment. The target turbulence intensity corresponding to the same wind speed segment in the adjacent sectors is determined as the target turbulence intensity corresponding to the target wind speed segment, thereby solving the problem of low turbulence intensity values ​​obtained by fitting high wind speed segments under complex terrain due to the small amount of measured data.

[0066] Step 105: If the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function.

[0067] Specifically, if the target correlation coefficient is greater than or equal to the preset correlation coefficient, the wind speed segment is substituted into the target fitting function according to the target fitting function, and the target turbulence intensity corresponding to the target wind speed segment can be calculated, thereby realizing the determination of the unmeasured turbulence intensity in the turbulence matrix, and then completing the turbulence matrix, avoiding the problem of insufficient data accuracy caused by filling in data with artificial experience, and solving the problem that the amount of measured data is small and the value of turbulence intensity obtained by fitting high wind speed segments under conventional terrain is too high.

[0068] The solution of the present application obtains wind speed data, wind direction data and measured turbulence intensity in a wind farm, and generates a turbulence matrix based on the wind speed data, wind direction data and measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensities corresponding to multiple wind speed segments in each wind direction sector in multiple wind direction sectors; the measured turbulence intensities corresponding to the wind speed segments that do not meet the measurement target in the turbulence matrix are eliminated, and the wind speed segments after the measured turbulence intensity is eliminated are determined as target wind speed segments; for each target wind speed segment, multiple wind speed segments in a target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined; if the target correlation coefficient is less than a preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix; if the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function. That is, the solution of the present application, when the wind direction and wind speed measurements in a wind farm do not meet the measurement targets, determines the corresponding output mode for the turbulence intensity based on the target correlation coefficient, thereby determining the turbulence intensity of the wind speed segment where the measurement abnormality occurs, thereby improving the accuracy of the turbulence intensity determination, thereby enhancing the accuracy of the wind resource assessment in the wind farm and improving the suitability of the site selection for the wind turbines.

[0069] Figure 2 is another flow chart of the method for determining turbulence intensity provided by the present application. Figure 1 Based on the illustrated embodiment and various optional implementation schemes, the process of generating the turbulence matrix is ​​described in detail. Figure 2 As shown, the method may include the following steps:

[0070] Step 201: Obtain wind speed data, wind direction data, and measure turbulence intensity in a wind farm.

[0071] Step 202, segmenting the wind speed data according to preset wind speed intervals to obtain a plurality of wind speed segments.

[0072] Specifically, the preset wind speed interval is a pre-set interval that evenly divides the wind speed. For example, the preset wind speed interval can be 10m / s. Taking the wind speed of 10m / s to 50m / s as an example, the wind speed data can be segmented according to the preset wind speed interval to obtain 4 wind speed segments, namely 10m / s to 20m / s, 20m / s to 30m / s, 30m / s to 40m / s and 40m / s to 50m / s.

[0073] Exemplarily, the actually measured wind speed data is divided into n integer intervals every X m / s to form a wind speed interval set {X1, X2, X3, ..., Xn}, that is, multiple wind speed segments are obtained, where the preset wind speed interval is X m / s.

[0074] Step 203: Taking the north wind direction in the wind direction data as zero degree, partitioning the wind direction data at preset angle intervals to obtain a plurality of wind direction sectors.

[0075] Specifically, the preset angle interval is a pre-set interval that evenly divides the wind direction. For example, the preset angle interval can be 90 degrees, and the wind direction in the north direction is taken as 0 degrees. Taking the wind direction from 0 degrees to 360 degrees, that is, the full wind direction, as an example, the wind direction data is segmented according to the preset angle interval to obtain 4 wind direction sectors, namely 0 degrees to 90 degrees, 90 degrees to 180 degrees, 180 degrees to 270 degrees, and 270 degrees to 360 degrees.

[0076] Exemplarily, the wind direction is divided into m sectors every Y degrees to form a wind direction sector set {Y1, Y2, Y3, ..., Ym}, where the data in the due north direction is treated as 0 degrees and should be placed in the first column.

[0077] Step 204 , generating a turbulence matrix according to the multiple wind direction sectors, the multiple wind speed segments corresponding to each wind direction sector, and the measured turbulence intensity corresponding to each wind speed segment.

[0078] Specifically, after determining multiple wind speed segments and multiple wind direction sectors, each wind direction sector corresponds to the same multiple wind speed segments. Therefore, a turbulence matrix is ​​generated according to the multiple wind speed segments corresponding to each wind direction sector in the multiple wind direction sectors, and the measured turbulence intensity corresponding to each wind speed segment in each wind direction sector.

[0079] Exemplarily, according to the wind speed interval set {X1, X2, X3, ..., Xn} and the wind direction sector set {Y1, Y2, Y3, ..., Ym}, an n×m matrix is ​​constructed, wherein the rows of the matrix represent the wind speed intervals and the columns represent the wind direction sectors. For each matrix element, the measured turbulence intensity corresponding to the wind speed interval under the wind direction sector is determined, thereby generating a turbulence matrix.

[0080] Step 205: remove the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determine the wind speed segment after removing the measured turbulence intensity as the target wind speed segment.

[0081] Step 206, for each target wind speed segment, multiple wind speed segments in the target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and determine a target correlation coefficient between the target fitting function and the measured turbulence intensity.

[0082] Step 207: If the target correlation coefficient is less than the preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment.

[0083] Step 208: If the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function.

[0084] The solution of the present application generates rows and columns of the turbulence matrix based on wind speed data and wind direction data, divides the turbulence intensity more clearly, and then determines the turbulence intensity, thereby further improving the accuracy of the measurement data, thereby further enhancing the accuracy of wind resource assessment in wind farms and improving the suitability of siting of wind turbines.

[0085] Figure 3 is a schematic diagram of a turbulence intensity determination device provided in the present application, and the device is suitable for executing the turbulence intensity determination method provided in the present application. Figure 3 As shown, the device may specifically include:

[0086] The acquisition module 301 is used to acquire wind speed data, wind direction data and measured turbulence intensity in the wind farm, and generate a turbulence matrix based on the wind speed data, the wind direction data and the measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensities corresponding to multiple wind speed segments in each of the wind direction sectors in multiple wind direction sectors.

[0087] The elimination module 302 is used to eliminate the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determine the wind speed segment after eliminating the measured turbulence intensity as the target wind speed segment.

[0088] The coefficient determination module 303 is used to fit, for each target wind speed segment, multiple wind speed segments in the target sector corresponding to the target wind speed segment with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and determine a target correlation coefficient between the target fitting function and the measured turbulence intensity.

[0089] The first determination module 304 is used to determine the measured turbulence intensity of the adjacent wind speed segment as the target turbulence intensity corresponding to the target wind speed segment if the target correlation coefficient is less than a preset correlation coefficient; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix.

[0090] The second determination module 305 is configured to determine the target turbulence intensity corresponding to the target wind speed segment according to the target fitting function if the target correlation coefficient is greater than or equal to the preset correlation coefficient.

[0091] In one embodiment, the first determination module 304 is specifically used for: if the target correlation coefficient is less than the preset correlation coefficient, and the adjacent wind speed segment corresponds to a measured turbulence intensity, then the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; if the target correlation coefficient is less than the preset correlation coefficient, and the adjacent wind speed segment does not have a corresponding measured turbulence intensity, then the adjacent sector of the target sector corresponding to the target wind speed segment is determined; wherein the adjacent sector is a sector adjacent to the target sector in the turbulence matrix; the target turbulence intensity corresponding to the same wind speed segment of the adjacent sector is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the wind speed interval of the same wind speed segment is the same as that of the target wind speed segment.

[0092] In one embodiment, the acquisition module 301, in terms of generating a turbulence matrix based on the wind speed data, the wind direction data and the measured turbulence intensity, is specifically used to: segment the wind speed data at preset wind speed intervals to obtain multiple wind speed segments; take the north wind direction in the wind direction data as zero degrees, and partition the wind direction data at preset angle intervals to obtain multiple wind direction sectors; generate the turbulence matrix based on multiple wind direction sectors, multiple wind speed segments corresponding to each wind direction sector, and the measured turbulence intensity corresponding to each wind speed segment.

[0093] In one embodiment, the measurement target of the elimination module 302 includes a number of initial measured turbulence intensities corresponding to the wind speed segment that is greater than or equal to a preset number.

[0094] In one embodiment, the coefficient determination module 303 is specifically used to: establish a measurement curve based on the multiple wind speed segments and the measured turbulence intensity corresponding to each wind speed segment in terms of determining the target correlation coefficient between the target fitting function and the measured turbulence intensity; and determine the target correlation coefficient between the target fitting function and the measured turbulence intensity based on the degree of correlation between the target fitting function and the measurement curve.

[0095] In one embodiment, the initial measured turbulence intensity of the elimination module 302 is obtained according to the turbulence intensity actually measured at the wind tower, the directional turbulence intensity calculated at the wind tower, the directional turbulence intensity calculated at the result point, the directional wind acceleration factor calculated at the wind tower, and the directional wind acceleration factor calculated at the result point.

[0096] In one embodiment, the directional turbulence intensity calculated by the elimination module 302 at the result point is determined according to the ambient turbulence intensity and the additional turbulence intensity at the result point.

[0097] The device of the present application obtains wind speed data, wind direction data and measured turbulence intensity in a wind farm, and generates a turbulence matrix based on the wind speed data, wind direction data and measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensities corresponding to multiple wind speed segments in each wind direction sector in multiple wind direction sectors; the measured turbulence intensities corresponding to the wind speed segments that do not meet the measurement target in the turbulence matrix are eliminated, and the wind speed segments after the measured turbulence intensity is eliminated are determined as target wind speed segments; for each target wind speed segment, multiple wind speed segments in a target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined; if the target correlation coefficient is less than a preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix; if the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function. That is, the solution of the present application, when the wind direction and wind speed measurements in a wind farm do not meet the measurement targets, determines the corresponding output mode for the turbulence intensity based on the target correlation coefficient, thereby determining the turbulence intensity of the wind speed segment where the measurement abnormality occurs, thereby improving the accuracy of the turbulence intensity determination, thereby enhancing the accuracy of the wind resource assessment in the wind farm and improving the suitability of the site selection for the wind turbines.

[0098] The present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for determining turbulence intensity provided in any of the above embodiments is implemented.

[0099] The present application also provides a computer-readable medium having a computer program stored thereon, and when the program is executed by a processor, the method for determining turbulence intensity provided in any of the above embodiments is implemented.

[0100] Reference below Figure 4 , which shows a structural schematic diagram of an electronic device 400 suitable for implementing the present application. Figure 4 The electronic device shown is only an example and should not bring any limitation to the function and scope of use of the present application.

[0101] like Figure 4As shown, the electronic device 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage part 408 into a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 are also stored. The CPU 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0102] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.

[0103] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 409, and / or installed from the removable medium 411. When the computer program is executed by the central processing unit (CPU) 401, the above-mentioned functions defined in the system of the present application are executed.

[0104] It should be noted that the computer-readable medium shown in the present application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0105] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the above-mentioned module, program segment or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0106] The modules and / or units described in this application may be implemented by software or hardware. The modules and / or units described may also be arranged in a processor, for example, it may be described as follows: a processor includes an acquisition module, a removal module, a coefficient determination module, a first determination module, and a second determination module. The names of these modules do not, in some cases, constitute limitations on the modules themselves.

[0107] As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the above embodiment; or may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device performs the following operations:

[0108] The wind speed data, wind direction data and measured turbulence intensity in the wind farm are obtained, and a turbulence matrix is ​​generated according to the wind speed data, wind direction data and measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensities corresponding to the multiple wind speed segments in each wind direction sector in the multiple wind direction sectors; the measured turbulence intensities corresponding to the wind speed segments that do not meet the measurement target in the turbulence matrix are eliminated, and the wind speed segments after the measured turbulence intensity is eliminated are determined as the target wind speed segments; for each target wind speed segment, multiple wind speed segments in the target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined; if the target correlation coefficient is less than a preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is the wind speed segment adjacent to the target wind speed segment in the turbulence matrix; if the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function.

[0109] According to the technical solution of the present application, wind speed data, wind direction data and measured turbulence intensity in a wind farm are obtained, and a turbulence matrix is ​​generated based on the wind speed data, wind direction data and measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensities corresponding to multiple wind speed segments in each wind direction sector in multiple wind direction sectors; the measured turbulence intensities corresponding to the wind speed segments that do not meet the measurement target in the turbulence matrix are eliminated, and the wind speed segments after the measured turbulence intensity is eliminated are determined as target wind speed segments; for each target wind speed segment, multiple wind speed segments in a target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined; if the target correlation coefficient is less than a preset correlation coefficient, the measured turbulence intensity of an adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix; if the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function. That is, the solution of the present application, when the wind direction and wind speed measurements in a wind farm do not meet the measurement targets, determines the corresponding output mode for the turbulence intensity based on the target correlation coefficient, thereby determining the turbulence intensity of the wind speed segment where the measurement abnormality occurs, thereby improving the accuracy of the turbulence intensity determination, thereby enhancing the accuracy of the wind resource assessment in the wind farm and improving the suitability of the site selection for the wind turbines.

[0110] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements a method for determining turbulence intensity as provided in any embodiment of the present application.

[0111] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present application, and the programming language includes an object-oriented programming language, such as Java, Smalltalk, C++, and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on the remote computer, or completely on the remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0112] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.

[0113] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for determining turbulence intensity, characterized in that: The method comprises: Acquire wind speed data, wind direction data and measured turbulence intensity in the wind farm, and generate a turbulence matrix according to the wind speed data, the wind direction data and the measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensity corresponding to multiple wind speed segments of each wind direction sector in multiple wind direction sectors; Eliminating the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determining the wind speed segment after eliminating the measured turbulence intensity as the target wind speed segment; For each of the target wind speed segments, multiple wind speed segments in a target sector corresponding to the target wind speed segment are fitted with the measured turbulence intensity corresponding to each of the wind speed segments to obtain a target fitting function, and a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined; If the target correlation coefficient is less than the preset correlation coefficient, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix; If the target correlation coefficient is greater than or equal to the preset correlation coefficient, the target turbulence intensity corresponding to the target wind speed segment is determined according to the target fitting function.

2. The method according to claim 1, characterized in that If the target correlation coefficient is less than the preset correlation coefficient, determining the turbulence intensity of the adjacent wind speed segment as the target turbulence intensity corresponding to the target wind speed segment includes: If the target correlation coefficient is less than the preset correlation coefficient, and the adjacent wind speed segment corresponds to a measured turbulence intensity, the measured turbulence intensity of the adjacent wind speed segment is determined as the target turbulence intensity corresponding to the target wind speed segment; If the target correlation coefficient is less than the preset correlation coefficient and there is no corresponding measured turbulence intensity in the adjacent wind speed segment, then determining an adjacent sector of the target sector corresponding to the target wind speed segment; wherein the adjacent sector is a sector in the turbulence matrix adjacent to the target sector; The target turbulence intensity corresponding to the same wind speed segment of the adjacent sectors is determined as the target turbulence intensity corresponding to the target wind speed segment; wherein the wind speed interval of the same wind speed segment is the same as that of the target wind speed segment.

3. The method according to claim 1, characterized in that The generating a turbulence matrix according to the wind speed data, the wind direction data and the measured turbulence intensity comprises: Segmenting the wind speed data according to preset wind speed intervals to obtain a plurality of wind speed segments; Taking the north wind direction in the wind direction data as zero degree, partitioning the wind direction data at preset angle intervals to obtain a plurality of wind direction sectors; The turbulence matrix is ​​generated according to a plurality of wind direction sectors, a plurality of wind speed segments corresponding to each of the wind direction sectors, and a measured turbulence intensity corresponding to each wind speed segment.

4. The method according to claim 1, characterized in that: The measurement target includes that the number of initial measured turbulence intensities corresponding to the wind speed segment is greater than or equal to a preset number.

5. The method according to claim 1, characterized in that The determining of the target correlation coefficient between the target fitting function and the measured turbulence intensity comprises: Establishing a measurement curve according to the plurality of wind speed segments and the measured turbulence intensity corresponding to each of the wind speed segments; According to the degree of correlation between the target fitting function and the measurement curve, a target correlation coefficient between the target fitting function and the measured turbulence intensity is determined.

6. The method according to claim 4, characterized in that The initial measured turbulence intensity is obtained according to the turbulence intensity actually measured at the wind tower, the directional turbulence intensity calculated at the wind tower, the directional turbulence intensity calculated at the result point, the directional wind acceleration factor calculated at the wind tower and the directional wind acceleration factor calculated at the result point.

7. The method according to claim 6, characterized in that The directional turbulence intensity calculated at the result point is determined according to the ambient turbulence intensity and the additional turbulence intensity at the result point.

8. A device for determining turbulence intensity, characterized in that: The device comprises: An acquisition module is used to acquire wind speed data, wind direction data and measured turbulence intensity in a wind farm, and generate a turbulence matrix according to the wind speed data, the wind direction data and the measured turbulence intensity; wherein the turbulence matrix is ​​used to characterize the measured turbulence intensity corresponding to multiple wind speed segments of each wind direction sector in multiple wind direction sectors; A removal module, used to remove the measured turbulence intensity corresponding to the wind speed segment that does not meet the measurement target in the turbulence matrix, and determine the wind speed segment after removing the measured turbulence intensity as the target wind speed segment; A coefficient determination module is used to fit, for each target wind speed segment, a plurality of wind speed segments in a target sector corresponding to the target wind speed segment with the measured turbulence intensity corresponding to each wind speed segment to obtain a target fitting function, and determine a target correlation coefficient between the target fitting function and the measured turbulence intensity; A first determination module, configured to determine the measured turbulence intensity of the adjacent wind speed segment as the target turbulence intensity corresponding to the target wind speed segment if the target correlation coefficient is less than a preset correlation coefficient; wherein the adjacent wind speed segment is a wind speed segment adjacent to the target wind speed segment in the turbulence matrix; The second determination module is used to determine the target turbulence intensity corresponding to the target wind speed segment according to the target fitting function if the target correlation coefficient is greater than or equal to the preset correlation coefficient.

9. 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, the turbulence intensity determination method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for determining turbulence intensity as claimed in any one of claims 1 to 7 is implemented.

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