Three-dimensional wind field construction method, system and storage medium based on wind profiler radar

Abstract

The present invention provides a method, system, and storage medium for constructing a three-dimensional wind field based on wind profiler radars, relating to the technical field of three-dimensional wind field construction. The method comprises the following steps: S1. acquiring horizontal and vertical wind data from each wind profiler radar; S2. correcting the wind speed vectors at each height along the vertical wind profile based on known wind profiler station location information and the distribution of the horizontal and vertical wind data along the vertical height; S2. after correction, adaptively resampling the wind speed vectors along the vertical wind profiles to obtain wind speed data at the same height level; and S3. based on the wind speed data at the same height level, constructing a three-dimensional wind field using a distance-weighted approach by networking wind profiler radars. This method can overcome the effects of the Earth's curvature on wind field construction results.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional wind field construction, and in particular to a three-dimensional wind field construction method, system and storage medium based on wind profiler radar. Background Art

[0002] Wind observation is a crucial step in climatology and meteorology research, as wind is the primary driving force behind atmospheric water circulation, air-sea exchange, aerosol transport, and weather changes. Therefore, the role of atmospheric wind is indispensable to human life and production. Observing wind distribution at various atmospheric levels is crucial for improving the reliability of weather forecasts, combating severe weather events, monitoring airflow at airports, and optimizing aircraft routes. Therefore, obtaining accurate and realistic three-dimensional wind fields is essential.

[0003] Currently, most three-dimensional wind field inversion algorithms use multi- or single-step Doppler weather wind profiler radars. While existing multi-Doppler weather wind profiler radar wind field inversion technology is mature and provides good results, the lack of tracer particles under clear sky conditions prevents weather wind profiler radars from obtaining complete wind field information, limiting their applicability. In contrast, wind profiler radars use microwave remote sensing to detect high-altitude wind fields by receiving and processing information returned by electromagnetic beams under the influence of the uneven vertical structure of the atmosphere. Under clear sky conditions, they can monitor the speed, direction, and structural constants of the atmosphere with high vertical resolution, making them a new generation of high-performance atmospheric monitoring equipment.

[0004] Although some provinces or cities have multiple wind profiler radars spaced a certain distance apart, providing the conditions for inverting large-scale wind fields through wind profiler radar networking, research on wind profiler radar networking for joint wind field inversion is currently in its preliminary stages and still has some shortcomings:

[0005] a) The area of ​​a 3D wind field constructed using a network of wind profiler radars is large, and the curvature of the earth will affect it. Existing algorithms for constructing 3D wind fields using a network of wind profiler radars ignore the impact of the earth's curvature on the wind field construction results.

[0006] b) Currently, the algorithm for constructing a three-dimensional wind field using a network of wind profiler radars is usually linear function fitting. Therefore, the algorithm for constructing a three-dimensional wind field using a network of wind profiler radars must use a certain number of wind profiler radars (4 or more), and only three of them are needed to construct a three-dimensional wind field.

[0007] c) Currently, most algorithms for constructing three-dimensional wind fields using wind profiler radar networks require that the distance libraries of the wind profiler radars be of equal length, which results in low utilization of the horizontal and vertical wind data of the wind profiler radars.

[0008] The current algorithm for constructing a three-dimensional wind field using a network of wind profiler radars has some restrictions on the altitude of the wind profiler radars. The actual wind profiler radars may not meet the requirements, making the current algorithm difficult to apply in actual business. Summary of the Invention

[0009] The present invention provides a three-dimensional wind field construction method, system and storage medium based on wind profiler radar, which can overcome the influence of the earth's curvature on the wind field construction results.

[0010] To achieve the above object, the present invention adopts the following technical solutions:

[0011] A first aspect of an embodiment of the present invention provides a three-dimensional wind field construction method based on a wind profiler radar, comprising the following steps:

[0012] S1. Obtain wind profiler radar horizontal wind and vertical wind data for each wind profiler radar;

[0013] S2. Correct the wind speed vector at each height on the vertical wind profile based on the known wind profile radar site location information and the vertical distribution of the wind profile radar horizontal wind and vertical wind data;

[0014] S3. After correction, adaptively resample the wind speed vector on the vertical wind profile to obtain wind speed data at the same altitude layer;

[0015] S4. Based on the wind speed data at the same altitude layer, a three-dimensional wind field is constructed by networking wind profiler radars and adopting a distance-weighted method.

[0016] In some embodiments, S2 includes:

[0017] S21. Establishing a geocentric coordinate system;

[0018] S22. Based on the geocentric coordinate system, determine the local coordinate system of each wind profiler radar location;

[0019] S23. The local coordinate system of one wind profiler radar is used as a reference coordinate system, and the local coordinate systems of the remaining wind profiler radars are converted to the reference coordinate system;

[0020] S24. After conversion, the wind speed vector of each wind profiler radar is corrected.

[0021] In some embodiments, in S23, Formula 1, Formula 2, and Formula 3 are used to perform coordinate system conversion; Formula 1:

[0022]

[0023] Formula 2:

[0024]

[0025] Formula 3:

[0026]

[0027] in, are the unit vectors corresponding to the three axes of the geocentric coordinate system; φ and θ are the latitude and longitude of the wind profiler radar corresponding to the reference coordinate system; are the unit vectors corresponding to the three axes of the reference coordinate system; φ′ and θ′ are the latitude and longitude of the wind profiler radar corresponding to the local coordinate system to be converted; are the unit vectors corresponding to the three axes of the local coordinate system to be transformed; K is the transformation matrix, K = B2B1 -1 , B1 and B2 are intermediate parameters.

[0028] In some embodiments, in S24, the wind speed vector is corrected using Formula 4, Formula 5, and Formula 6;

[0029] Formula 4:

[0030] Formula 5:

[0031] Formula 6: [uvw]=[u′v′w′]B2B1 -1 ;

[0032] Wherein, V′ is the wind speed vector to be corrected, [u′v′w′] is the component of the wind speed vector to be corrected, and [uvw] is the component of the wind speed vector after correction.

[0033] In some embodiments, S3 includes:

[0034] S31 obtains the wind speed and / or wind direction at each height of the vertical wind profile;

[0035] S32. Calculate the height difference between adjacent heights, as well as the wind speed difference and / or wind direction difference;

[0036] S33 calculates the rate of change of wind speed and / or wind direction with height, the rate of change WS1 is equal to the ratio of the wind speed difference to the height difference, the rate of change WS2 is equal to the ratio of the wind direction difference to the height difference;

[0037] S34. Establish the fitting function of components u, v, and w with respect to height:

[0038] u=α u0 +α u1 h+α u2 h 2 +α u3 h 3 +…+αun h n ;

[0039] v=α v0 +α v1 h+α v2 h 2 +α v3 h 3 +…+α vn h n ;

[0040] w=α w0 +α w1 h+α w2 h 2 +α w3 h 3 +…+α wn h n ;

[0041] Among them, h is the height, α u0 ...α un , α v0 ...α vn , α w0 ...α wn is the resampling parameter, and n is the order of the fitting function;

[0042] S35. Compare the change rate WS1 and / or the change rate WS2 with the preset threshold value to determine the order of the fitting function; when it is less than the preset threshold value, n=1; when it is equal to the preset threshold value, n=2; when it is greater than the preset threshold value, n=3;

[0043] S36. Determine the resampling parameters using the least squares method;

[0044] S37. Based on the determined order of the fitting function and the determined resampling parameter, obtain an adaptive fitting function of the components u, v, and w with respect to height;

[0045] S38. Slice each wind profiler radar at any height, divide it into grids at the height, substitute the height of each grid into the fitting function of the adaptive components u, v, and w with respect to the height for resampling, and obtain the components of the wind speed vector at the same height.

[0046] In some embodiments, the process of determining the resampling parameters using the least squares method in S36 is as follows:

[0047] Obtain the height value of each layer of the vertical wind profile detected by each wind profile radar, form it into a matrix H according to formula 13, and the vectors of the components corresponding to the height are Their forms are as shown in Equation 14, Equation 15 and Equation 16;

[0048] Formula 13:

[0049]

[0050] Formula 14:

[0051] Formula 15:

[0052] Formula 16:

[0053] Where m is the height layer of the profile obtained by wind profiler radar detection;

[0054] Then we can get the parameters of each fitting function and Such as formula 17, formula 18 and formula 19;

[0055] Formula 17:

[0056] Formula 18:

[0057] Formula 19:

[0058] In some embodiments, in S4, the wind speed component fitting model is used to calculate the wind speed component values ​​of all horizontal grids at each height grid to complete the construction of the three-dimensional wind field;

[0059] The fitting model of the wind speed component is:

[0060]

[0061] Where N is the number of wind profiler radars; u i (x i ,y i ,z)、v i (x i ,y i ,z)、w i (x i ,y i ,z) are the resampled values ​​of each wind profiler radar on the height grid z; x and y are the coordinates on each divided grid; x i and y i is the coordinate of each wind profiler radar on the horizontal grid; a i (x,y) is the weight of the estimated grid and each wind profiler radar.

[0062] In some embodiments, the weight a is determined using the following formula:i (x,y):

[0063]

[0064] Among them, x i and y i is the coordinate of each wind profiler radar on the horizontal plane, d i (x,y) is the distance between the estimated grid and each wind profiler radar.

[0065] A second aspect of an embodiment of the present invention provides a three-dimensional wind field construction system based on a wind profiler radar, comprising:

[0066] A data acquisition module, used to acquire wind profiler radar horizontal wind and vertical wind data of each wind profiler radar;

[0067] A wind profile data determination module is used to determine the wind profile data of the corresponding position of each wind profile radar based on the horizontal wind and vertical wind data of the wind profile radar;

[0068] A correction module, configured to correct the wind speed vector on the vertical wind profile based on the wind profile data;

[0069] Adaptive resampling module, which is used to adaptively resample the wind speed vector on the vertical wind profile after correction to obtain wind speed data at the same altitude layer;

[0070] The three-dimensional wind field construction module is used to construct a three-dimensional wind field based on the wind speed data at the same altitude layer through a wind profile radar network and a distance-weighted method.

[0071] A third aspect of an embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions, the computer executes the three-dimensional wind field construction method based on wind profiler radar as described above.

[0072] In summary, the present invention has at least the following beneficial effects:

[0073] The present invention can overcome the influence of the earth's curvature on the wind field construction result. Even if the distance between the wind profiler radars is far and the influence of the earth's curvature is introduced, the coordinate system of each wind profiler radar can be converted and the measured wind speed can be corrected.

[0074] The number of wind profiler radars used in the present invention can be any number (two or more), and it is not required that every three wind profiler radars must be networked.

[0075] The invention solves the data utilization problem of the wind profiler radar by processing the horizontal wind and vertical wind data of the wind profiler radar compatible with different library lengths.

[0076] The present invention has no requirements for the altitude of the wind profiler radar and can extract any area of ​​interest and altitude individually at the software level as needed to display more detailed wind field construction results. It can be effectively applied in business. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only 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.

[0078] Figure 1 The figure is a schematic diagram of the steps of the three-dimensional wind field construction method based on wind profiler radar involved in the present invention.

[0079] Figure 2 The figure is a flow chart of the method for constructing a three-dimensional wind field based on wind profiler radar involved in the present invention.

[0080] Figure 3 Schematic diagram of the geocentric coordinate system and the local coordinate system of the wind profiler radar involved in the present invention.

[0081] Figure 4 Schematic diagram of the high-resolution mapping result of the wind speed component in the vertical direction involved in the present invention.

[0082] Figure 5a This is a schematic diagram of the results of directly using the resolution of wind profiler radar detection results to construct a wind field involved in the present invention.

[0083] Figure 5b This is a schematic diagram of the results of wind field construction after improving the resolution through resampling involved in the present invention.

[0084] Figure 6a This is a schematic diagram of the effect of intercepting a horizontal plane at a vertical height with a resolution of 5000 meters in the wind farm construction involved in the present invention.

[0085] Figure 6b This is a schematic diagram of the effect of intercepting a horizontal plane at a vertical height with a resolution of 2000 meters in the wind farm construction involved in the present invention.

[0086] Figure 6c This is a schematic diagram of the effect of intercepting a horizontal plane at a vertical height with a resolution of 500 meters in the wind farm construction involved in the present invention.

[0087] Figure 7aThis is a schematic diagram of the effect of constructing a three-dimensional wind field using a wind profiler radar in wind field 1 involved in the present invention.

[0088] Figure 7b This is a schematic diagram of the effect of constructing a three-dimensional wind field using a wind profiler radar in wind field 2 involved in the present invention. DETAILED DESCRIPTION

[0089] Hereinafter, only certain exemplary embodiments are briefly described. As will be appreciated by those skilled in the art, the described embodiments may be modified in various ways without departing from the spirit or scope of the embodiments of the present invention. Therefore, the drawings and description are to be regarded as illustrative in nature and not restrictive.

[0090] The disclosure below provides many different embodiments or examples for implementing different structures of the embodiments of the present invention. In order to simplify the disclosure of the embodiments of the present invention, the components and configurations of specific examples are described below. Of course, these are merely examples and are not intended to limit the embodiments of the present invention. In addition, the embodiments of the present invention may repeat reference numerals and / or reference letters in different examples. Such repetition is for the purpose of simplicity and clarity and does not in itself indicate the relationship between the various embodiments and / or configurations discussed.

[0091] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0092] like Figure 1 As shown, a first aspect of an embodiment of the present invention provides a three-dimensional wind field construction method based on a wind profiler radar, comprising the following steps:

[0093] S1. Obtain wind profiler radar horizontal wind and vertical wind data for each wind profiler radar;

[0094] S2. Correct the wind speed vector at each height on the vertical wind profile based on the known wind profile radar site location information and the vertical distribution of the wind profile radar horizontal wind and vertical wind data;

[0095] S3. After correction, adaptively resample the wind speed vector on the vertical wind profile to obtain wind speed data at the same altitude layer;

[0096] S4. Based on the wind speed data at the same altitude layer, a three-dimensional wind field is constructed by networking wind profiler radars and adopting a distance-weighted method.

[0097] In some embodiments, S2 includes:

[0098] S21. Establishing a geocentric coordinate system;

[0099] S22. Based on the geocentric coordinate system, determine the local coordinate system of each wind profiler radar location;

[0100] S23. The local coordinate system of one wind profiler radar is used as a reference coordinate system, and the local coordinate systems of the remaining wind profiler radars are converted to the reference coordinate system;

[0101] S24. After conversion, the wind speed vector of each wind profiler radar is corrected.

[0102] In some embodiments, in S23, Formula 1, Formula 2, and Formula 3 are used to perform coordinate system conversion; Formula 1:

[0103]

[0104] Formula 2:

[0105]

[0106] Formula 3:

[0107]

[0108] in, are the unit vectors corresponding to the three axes of the geocentric coordinate system; φ and θ are the latitude and longitude of the wind profiler radar corresponding to the reference coordinate system; are the unit vectors corresponding to the three axes of the reference coordinate system; φ′ and θ′ are the latitude and longitude of the wind profiler radar corresponding to the local coordinate system to be converted; are the unit vectors corresponding to the three axes of the local coordinate system to be transformed; K is the transformation matrix, K = B2B1 -1 , B1 and B2 are intermediate parameters.

[0109] In some embodiments, in S24, the wind speed vector is corrected using Formula 4, Formula 5, and Formula 6;

[0110] Formula 4:

[0111] Formula 5:

[0112] Formula 6: [uvw]=[u′v′w′]B2B1 -1 ;

[0113] Wherein, V′ is the wind speed vector to be corrected, [u′v′w′] is the component of the wind speed vector to be corrected, and [uvw] is the component of the wind speed vector after correction.

[0114] In some embodiments, S3 includes:

[0115] S31 obtains the wind speed and / or wind direction at each height of the vertical wind profile;

[0116] S32. Calculate the height difference between adjacent heights, as well as the wind speed difference and / or wind direction difference, as shown in Formula 7 and Formula 8;

[0117] Formula 7: Δv = v2 - v1;

[0118] Formula 8: Δd=d2-d1;

[0119] Where v1 and v2 represent the wind speed at two adjacent heights, d1 and d2 represent the wind direction at two adjacent heights, and Δv and Δd are the wind speed and wind direction differences at two adjacent heights.

[0120] S33. Calculate the rate of change of wind speed and / or wind direction with height, where the rate of change WS1 is equal to the ratio of the wind speed difference to the height difference, and the rate of change WS2 is equal to the ratio of the wind direction difference to the height difference; as shown in Formula 9;

[0121] Formula 9:

[0122] S34. Establishing a fitting function of the components u, v, and w with respect to height: as shown in Formula 10, Formula 11, and Formula 12;

[0123] Formula 10: u = α u0 +α u1 h+α u2 h 2 +α u3 h 3 +…+α un h n ;

[0124] Formula 11: v = α v0 +α v1 h+α v2 h 2 +α v3 h 3 +…+α vn h n ;

[0125] Formula 12: w = α w0 +α w1 h+α w2 h 2 +α w3 h 3 +…+α wn h n ;

[0126] Among them, h is the height, α u0 ...α un , α v0...α vn , α w0 ...α wn is the resampling parameter, and n is the order of the fitting function;

[0127] S35. Compare the change rate WS1 and / or the change rate WS2 with the preset threshold value to determine the order of the fitting function; when it is less than the preset threshold value, n=1; when it is equal to the preset threshold value, n=2; when it is greater than the preset threshold value, n=3;

[0128] S36. Determine the resampling parameters using the least squares method;

[0129] S37. Based on the determined order of the fitting function and the determined resampling parameter, obtain an adaptive fitting function of the components u, v, and w with respect to height;

[0130] S38. Slice each wind profiler radar at any height, divide it into grids at the height, substitute the height of each grid into the fitting function of the adaptive components u, v, and w with respect to the height for resampling, and obtain the components of the wind speed vector at the same height.

[0131] In summary, the first step is to unify the altitude layers vertically. In this work, WS1 and WS2 are calculated using only the vertical wind profile data obtained by each wind profiler radar. This is solely related to the range bin length (the vertical height interval) (as shown in the formula). There is no determination of the rate of change in the horizontal direction. The next step is to construct the three-dimensional wind field.

[0132] In some embodiments, the process of determining the resampling parameters using the least squares method in S36 is as follows:

[0133] Obtain the height value of each layer of the vertical wind profile detected by each wind profile radar, form it into a matrix H according to formula 13, and the vectors of the components corresponding to the height are Their forms are as shown in Equation 14, Equation 15 and Equation 16;

[0134] Formula 13:

[0135]

[0136] Formula 14:

[0137] Formula 15:

[0138] Formula 16:

[0139] Where m is the height layer of the profile obtained by wind profiler radar detection;

[0140] Then we can get the parameters of each fitting function and Such as formula 17, formula 18 and formula 19;

[0141] Formula 17:

[0142] Formula 18:

[0143] Formula 19:

[0144] In some embodiments, in S4, the wind speed component fitting model is used to calculate the wind speed component values ​​of all horizontal grids at each height grid to complete the construction of the three-dimensional wind field;

[0145] The fitting models of the wind speed components are as shown in Formula 20, Formula 21 and Formula 22:

[0146] Formula 20:

[0147] Formula 21:

[0148] Formula 22:

[0149] Where N is the number of wind profiler radars; u i (x i ,y i ,z)、v i (x i ,y i ,z)、w i (x i ,y i ,z) are the resampled values ​​of each wind profiler radar on the height grid z; x and y are the coordinates on each divided grid; x i and y i is the coordinate of each wind profiler radar on the horizontal grid; a i (x,y) is the weight of the estimated grid and each wind profiler radar.

[0150] In some embodiments, the weight a is determined using the following formula: i (x,y):

[0151] Formula 23:

[0152] Formula 24:

[0153] Among them, x i and y iis the coordinate of each wind profiler radar on the horizontal plane, d i (x,y) is the distance between the estimated grid and each wind profiler radar.

[0154] A second aspect of an embodiment of the present invention provides a three-dimensional wind field construction system based on a wind profiler radar, comprising:

[0155] A data acquisition module, used to acquire wind profiler radar horizontal wind and vertical wind data of each wind profiler radar;

[0156] A wind profile data determination module is used to determine the wind profile data of the corresponding position of each wind profile radar based on the horizontal wind and vertical wind data of the wind profile radar;

[0157] A correction module, configured to correct the wind speed vector on the vertical wind profile based on the wind profile data;

[0158] Adaptive resampling module, which is used to adaptively resample the wind speed vector on the vertical wind profile after correction to obtain wind speed data at the same altitude layer;

[0159] The three-dimensional wind field construction module is used to construct a three-dimensional wind field based on the wind speed data at the same altitude layer through a wind profile radar network and a distance-weighted method.

[0160] A third aspect of an embodiment of the present invention provides a computer-readable storage medium, which stores computer instructions. When a computer reads the computer instructions, the computer executes the three-dimensional wind field construction method based on wind profiler radar as described above.

[0161] In order to more clearly describe the technical solution of the present invention, the technical concept of the present invention is as follows:

[0162] like Figure 2As shown, the basic process of the present invention is divided into four stages, the main contents of which are: based on the horizontal and vertical wind data obtained from the wind profiler radar, the wind speed vector on the vertical wind profile of each wind profiler radar is corrected, the wind speed in the wind profiler data of each wind profiler radar is adaptively resampled, and a large-scale three-dimensional wind field is constructed. Each wind profiler radar first needs to obtain wind profile data at the corresponding location; the wind speed vector at each height in the data of each wind profiler radar is corrected; then, the discrete wind profiler data at each wind profiler radar location, which may have different storage lengths, is adaptively resampled according to the dramatic changes in wind speed, converting the data in the discrete space of the wind profiler data into data in a continuous space, and then resampling to obtain data at the same height; finally, by networking the wind profiler radars, a distance-weighted method is used to complete the large-scale three-dimensional wind field construction. Finally, the three-dimensional wind field construction results within the coverage area of ​​all wind profiler radars are obtained, as well as the three-dimensional wind field construction results outside the coverage area.

[0163] 1. Correction of wind speed vector on vertical wind profile of each wind profile radar

[0164] This step is performed based on the wind vector (or wind speed components u, v, w) data for each range bin in the wind profile data obtained from each wind profiler radar. Each wind profiler radar coordinate is a local coordinate on a spherical surface, so the wind speed vector measured on the vertical wind profile is measured using the local coordinates of that location as a reference. However, due to the curvature of the earth, the X, Y, and Z axes of the coordinate systems of each wind profiler radar are no longer parallel. Therefore, the horizontal and vertical directions of the wind profiles measured by each wind profiler radar are no longer the same, resulting in different measurement heights and different definitions of wind speed directions between the wind profilers. In addition, the same coordinate system is also needed to construct a three-dimensional wind field, and the references for the wind speed vectors of each wind profiler radar are different on the spherical surface, so direct calculations will result in errors. If the distance between each wind profiler radar reaches more than tens of kilometers, the wind field construction result will be significantly different from the actual situation.

[0165] Therefore, in the present invention, before the wind field construction work, the wind speed component at each height of each wind profiler radar needs to be corrected according to the geocentric coordinate system as the reference coordinate system. The purpose is to overcome the influence of the earth's curvature and unify the measured wind speed to the same coordinate to facilitate the subsequent wind field construction work.

[0166] 1.1 Coordinate system regulations

[0167] Geocentric coordinate system: Figure 3 As shown, the center of the earth is the origin, the unit vector from the center of the earth to the North Pole is the Z axis, the direction from the center of the earth to the intersection of the 0° longitude line and the equator is the X axis, and the The direction is the Y axis.

[0168] The local coordinate system of the wind profiler radar location: Figure 3 As shown, the meteorological convention is that at any point on the ground, the local coordinate system X axis is agreed to run from west to east (denoted as X'), and the local coordinate system Y axis is agreed to run from south to north (denoted as Y'). Therefore, the X axis is tangent to the latitude of the point, and the Y axis is tangent to the longitude of the point. The local coordinate system Z axis (denoted as Z') is exactly the cross product direction of the local coordinate system X axis and the local coordinate system Y axis, that is, perpendicular to the ground at the point and upward.

[0169] 1.2 Provisions for wind speed components and local coordinate systems

[0170] like Figure 3 As shown in the figure, in the ground coordinate system, with the point where the wind profiler radar is located as the origin, the direction of the east tangent to the latitude is the direction of the X' axis, and the wind speed component u is measured accordingly; the direction of the north tangent to the longitude is the direction of the Y' axis, and the wind speed component v is measured accordingly; and the cross product direction of the X' axis and the Y' axis is the direction of the Z' axis, and the wind speed component w is measured accordingly.

[0171] 1.3 Convert local coordinates through the geocentric coordinate system

[0172] Assume that the unit vectors corresponding to the three axes of the geocentric coordinate system are The coordinate system of one of the wind profiler radars in the wind profiler radar network is selected as the reference coordinate system for the construction of the three-dimensional wind field. The data of the other wind profiler radars need to be converted according to this reference coordinate system. The longitude and latitude of this wind profiler radar are φ and θ respectively, and the unit vectors corresponding to the three axes of the coordinate system are The latitudes of the wind profiler radar that need to be converted to the corresponding coordinates are φ′ and θ′, and the unit vectors corresponding to the three axes of the coordinate system are Their transformation relationships with the unit vector of the geocentric coordinate system are shown in Formula 1 and Formula 2.

[0173] Therefore, the conversion matrix K=B2B1 required to convert the local coordinate system of the wind profiler radar to the reference coordinate system can be obtained through the geocentric coordinate system. -1 , the coordinate system conversion process is as shown in Formula 3.

[0174] According to formula 1 and formula 2, the local coordinate system of each wind profiler radar can be converted to the reference coordinate system with the geocentric coordinate system as the intermediary, so the conversion matrix K used by each wind profiler radar is obtained. i (i is 1 to (N-1), N is the number of wind profiler radars).

[0175] 1.4 Wind speed vector correction

[0176] Then, through the geocentric coordinates as the medium, the conversion matrix K of the local coordinate system of each wind profiler radar is converted to the reference coordinate system i After that, the work that needs to be done is to correct the wind speed vectors measured by each wind profiler radar. Take the wind profile data measured by one of the wind profiler radars that needs to correct the wind vector as an example, let the wind speed vector of a certain distance library in the measured wind profiler data be V', and the unit vectors corresponding to the three axes of the local coordinate system where the wind profiler radar is located be It can be expressed as Formula 4. Formula 5 can be obtained through Formula 3. Finally, the components of the wind speed vector V after the unified coordinate system are obtained through Formula 6.

[0177] 2. Adaptive resampling of wind speed on vertical wind profile after wind speed vector correction

[0178] After wind speed vector correction, the height layers of each wind speed vector measured by each wind profiler radar are still discrete. Furthermore, due to the different altitudes and range library parameters set for each wind profiler radar, the effective wind speed detected may be staggered at different heights, making it impossible to complete the three-dimensional wind field construction at each height layer. Therefore, it is necessary to resample the wind speed data at different height layers of each wind profiler radar to re-unify the wind speed data at the same height layer to facilitate the subsequent three-dimensional wind field construction.

[0179] In general, using a linear function to describe wind field relationships in continuous space is effective and accurate. Linear fitting is also highly robust and can effectively handle outliers and noise caused by interference during wind profiler radar detection. Therefore, directly using linear fitting for resampling is feasible in this case. However, if wind speeds vary dramatically within a given moment, the linear function may not be able to accurately describe the wind field relationship, resulting in underfitting.

[0180] Therefore, the present invention proposes to use a polynomial function for adaptive resampling. When using a polynomial function for description, if the order is too high, overfitting is likely to occur. Therefore, it is first necessary to determine the severity of the wind speed change at that moment and adaptively adjust the order of the polynomial function. If the wind speed changes more drastically, the order of the polynomial function can be increased according to the severity of the wind change to avoid underfitting. In addition, the polynomial function fitting operation efficiency is high, which is crucial for processing a large amount of wind speed data on the profiles of multiple wind profiler radars at the same time.

[0181] 2.1 Judgment of severe wind speed

[0182] The severity of wind speed changes at each height along the vertical wind profile can be described by the rate of change of wind speed (and / or direction) with height in the air flow. This is divided into two types: the rate of change of wind speed (and / or direction) in the vertical direction and the rate of change of wind speed (and / or direction) in the horizontal direction.

[0183] The wind speed and direction differences between two adjacent heights can be calculated, as shown in Formulas 7 and 8. Here, v1 and v2 represent the wind speed at two adjacent heights, respectively; d1 and d2 represent the wind direction at two adjacent heights, respectively. Δv and Δd are then the wind speed and direction differences at two adjacent heights. Using these two variables, we can calculate the wind speed intensity at each adjacent height, as shown in Formula 9. ΔH is the difference between two adjacent heights, which is directly equivalent to the range bin length set for the wind profiler radar.

[0184] 2.2 Adaptive Resampling

[0185] For a single wind profiler radar, the polynomial function model is as shown in Formulas 10 to 12, and the fitting functions of the u, v, and w components with respect to height are obtained respectively through these formulas; where h is the height, α u0 , α u1 , α u2 , ... and other parameters are the parameters that need to be solved when resampling the u component; the parameters of the v component and the w component are the same.

[0186] According to the WS value calculated above, the adaptive order for severe wind speed is determined. When the WS value is less than or equal to 5m / s, the polynomial function model takes the first order, taking the u component as an example, that is, u=α u0 +α u1 h; When the WS value is greater than 5m / s and less than or equal to 10m / s, the polynomial function model takes the second order, taking the u component as an example, that is, u=α u0 +α u1 h+α u2 h 2 When the WS value is greater than 10m / s, the polynomial function model takes the third order, taking the u component as an example, that is, u=α u0 +α u1 h+α u2 h 2 +α u3 h 3 .

[0187] In order to facilitate the solution of parameters, no matter how many orders the polynomial function has, its parameters are set in vector form The method for solving the parameters is the least square method. First, we need to obtain the height value of each layer of the vertical wind profile detected by each wind profile radar, and form it into a matrix H according to formula 13. And the vectors of the components corresponding to the height are Their forms are as shown in formula 14 to formula 16. Then the parameters of each fitting function can be obtained respectively Such as Formula 17 to Formula 19.

[0188] After adaptively obtaining the polynomial fitting functions for each component, resampling is performed. Slicing each wind profiler radar at any altitude yields valid wind speeds. Ultimately, the desired height grid is divided, and the height of each grid is directly applied to the adaptively fitted function for resampling. This results in uniform wind speeds at the same high level, facilitating subsequent 3D wind field construction.

[0189] 3. Large-scale three-dimensional wind farm construction

[0190] After adaptive resampling of the profile height, the horizontal wind vector information of each wind profiler radar at the same altitude layer can be easily obtained, that is, vector On the horizontal scale, these vector information are sparsely distributed and cannot fully reflect the wind field information. Therefore, after dividing the horizontal grid, it is necessary to calculate the grid with missing data by weighting the measured points.

[0191] The present invention can adaptively adjust the weighted value in the three-dimensional wind field construction process according to the number of wind profiler radars and the distance between each wind profiler radar. By setting a function related to the distance, the influence of the distance of the effective wind speed measurement point on the estimated point is determined. Compared with the method of directly using linear fitting to construct a three-dimensional wind field, the method of the present invention can take the distance between the wind speed measurement points into account, and there is no need to limit the number of wind profiler radars (the linear fitting method requires three or more wind profiler radars, while the two wind profiler radars of the present invention can also complete the construction of the three-dimensional wind field). The constructed three-dimensional wind field is also accurate and effective.

[0192] Assume that the fitting models of the wind speed components are as shown in Formula 20 to Formula 22 respectively.

[0193] Where N is the number of wind profiler radars; u i (x i ,y i ,z),v i (x i ,y i ,z),w i (x i ,y i,z) are the measured values ​​(resampled values) of each wind profiler radar on the height grid z; x, y are the coordinates on each divided grid; x i ,y i is the coordinate of each wind profiler radar on the horizontal grid; a i (x,y) is the weight of the estimated grid and each wind profiler radar. The weight is defined as shown in Formula 23 and Formula 24.

[0194] The distance weighting algorithm adopted in the present invention is inverse exponential weighting. i and y i is the coordinate of each wind profiler radar on the horizontal plane, d i (x,y) is the distance between the estimated grid and each wind profiler radar.

[0195] Finally, by using Formulas 20 to 22, the wind speed component values ​​of all horizontal grids at each height grid z are calculated, thus completing the construction of the three-dimensional wind field.

[0196] In a specific embodiment, taking a single wind profile radar as an example, the wind profile is resampled in the vertical direction, and the result of resampling the wind speed in the vertical direction is as follows: Figure 4 , can be obtained from Figure 4 The previously discrete and low-resolution wind speed components at each altitude level have become dense and accurate after high-resolution mapping. Furthermore, extrapolation results within a small range beyond the altitude levels detected by the wind profiler radar are also more accurate and reliable.

[0197] Taking five wind profiler radars as an example, the three-dimensional wind field of the wind profiler radar is constructed. Figure 5a It is the result of directly using the resolution of wind profiler radar detection results to analyze the wind field. Figure 5b This is the result of resampling to achieve higher resolution and then reconstructing the wind field. This results in a denser 3D wind field, allowing for a more detailed and accurate display of wind field changes within the wind profiler radar's coverage area. This can be adjusted dynamically based on actual computing power and demand.

[0198] The present invention can adjust the resolution and coverage of the wind farm construction according to actual needs. Figure 6a 、 Figure 6b 、 Figure 6c This image shows the effect of capturing horizontal planes at different vertical resolutions during wind farm construction: 5,000 meters, 2,000 meters, and 500 meters, respectively. As the resolution increases, the details within the wind farm become richer, and this can be adjusted dynamically based on actual computing power and demand.

[0199] The present invention is also applicable to wind field construction of various complexities. Taking five wind profiler radars as an example, three-dimensional wind field construction of wind profiler radars is performed under different weather conditions. Figure 7a and Figure 7b It is the wind field construction effect of different complexity. Even if vortices appear in the wind field, the present invention can construct them finely. Figure 7a The wind speeds measured at a single point are all relatively small (wind field 1: the wind field structure may be relatively simple), and Figure 7b The wind speed measured at a single point is relatively high (wind field 2: the wind field structure may be complex).

[0200] The above embodiments are intended to illustrate the present invention, not to limit the present invention. Therefore, changes in illustrative values ​​or substitutions of equivalent components should still fall within the scope of the present invention.

[0201] From the above detailed description, it will be clear to those skilled in the art that the present invention can indeed achieve the aforementioned objectives and is in compliance with the provisions of the Patent Law.

[0202] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic inventive concepts. Therefore, the appended claims are intended to be interpreted as covering the preferred embodiments and all changes and modifications that fall within the scope of the invention. The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. It should be noted that any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

[0203] It should be noted that the above description of the relevant processes is for illustration and purpose only and does not limit the scope of application of this specification. For those skilled in the art, various modifications and changes can be made to the processes under the guidance of this specification. However, such modifications and changes are still within the scope of this specification.

[0204] The basic concepts have been described above. It will be apparent to those skilled in the art after reading this application that the above disclosures are merely illustrative and do not constitute limitations on this application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements, and amendments to this application. Such modifications, improvements, and amendments are suggested in this application and remain within the spirit and scope of the exemplary embodiments of this application.

[0205] At the same time, this application uses specific terms to describe the embodiments of this application. For example, "one embodiment," "an embodiment," and / or "some embodiments" refer to a certain feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that "one embodiment," "an embodiment," or "an alternative embodiment" mentioned twice or more in different places in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application may be appropriately combined.

[0206] In addition, it will be understood by those skilled in the art that various aspects of the present application can be illustrated and described by a number of patentable categories or situations, including any new and useful combination of processes, machines, products or substances, or any new and useful improvements thereto. Therefore, various aspects of the present application can be implemented entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software can all be referred to as "units", "modules" or "systems". In addition, various aspects of the present application can take the form of a computer program product embodied in one or more computer-readable media, wherein computer-readable program code is contained therein.

[0207] The computer program code required for the operation of each part of the application can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, conventional procedural programming languages ​​such as C programming language, VisualBasic, Fortran2103, Perl, COBOL2102, PHP, ABAP, dynamic programming languages ​​such as Python, Ruby and Groovy or other programming languages. The program code can be run completely on the user's computer, or run on the user's computer as an independent software package, or run partly on the user's computer and partly on a remote computer, or run completely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network form, such as a local area network (LAN) or a wide area network (WAN), or be connected to an external computer (such as by the Internet), or in a cloud computing environment, or used as a service such as software as a service (SaaS).

[0208] In addition, unless expressly stated in the claims, the order of the processing elements and sequences described in this application, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some embodiments of the invention that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this application. For example, although the implementation of the various components described above can be embodied in a hardware device, it can also be implemented as a pure software solution, for example, installation on an existing server or mobile device.

[0209] Similarly, it should be noted that in order to simplify the presentation of this disclosure and thereby facilitate understanding of one or more of the invention's embodiments, the foregoing descriptions of the embodiments of this disclosure sometimes combine multiple features into a single embodiment, figure, or description thereof. However, this approach should not be interpreted as reflecting an intention that the claimed subject matter requires more features than expressly recited in each claim. Rather, the subject matter of the invention may possess fewer features than the single embodiment described above.

Claims

1. A three-dimensional wind field construction method based on wind profiler radar, characterized in that: The process includes the following steps: S1. Obtain wind profiler radar horizontal wind and vertical wind data for each wind profiler radar; S2. Correct the wind speed vector at each height on the vertical wind profile based on the known wind profile radar site location information and the vertical distribution of the wind profile radar horizontal wind and vertical wind data; S3. After correction, adaptively resample the wind speed vector on the vertical wind profile to obtain wind speed data at the same altitude layer; S4. Based on the wind speed data at the same altitude, a three-dimensional wind field is constructed by a wind profiler radar network using a distance-weighted method; S2 includes: S21. Establishing a geocentric coordinate system; S22. Based on the geocentric coordinate system, determine the local coordinate system of each wind profiler radar location; S23. The local coordinate system of one wind profiler radar is used as a reference coordinate system, and the local coordinate systems of the remaining wind profiler radars are converted to the reference coordinate system; S24. After conversion, the wind speed vector of each wind profiler radar is corrected.

2. The three-dimensional wind field construction method based on wind profiler radar according to claim 1, characterized in that: In S23, the coordinate system is transformed using Formula 1, Formula 2, and Formula 3; Formula 1: Formula 2: Formula 3: in, are the unit vectors corresponding to the three axes of the geocentric coordinate system; φ and θ are the latitude and longitude of the wind profiler radar corresponding to the reference coordinate system; are the unit vectors corresponding to the three axes of the reference coordinate system; φ′ and θ′ are the latitude and longitude of the wind profiler radar corresponding to the local coordinate system to be converted; are the unit vectors corresponding to the three axes of the local coordinate system to be transformed; K is the transformation matrix, K = B2B1 -1 , B1 and B2 are intermediate parameters.

3. The three-dimensional wind field construction method based on wind profiler radar according to claim 2, characterized in that: In S24, the wind speed vector is corrected using Formula 4, Formula 5, and Formula 6; Formula 4: Formula 5: Formula 6: [u v w]=[u′ v′ w′]B2B1 -1 ; Wherein, V′ is the wind speed vector to be corrected, [u′ v′ w′] is the component of the wind speed vector to be corrected, and [uvw] is the component of the wind speed vector after correction.

4. The three-dimensional wind field construction method based on wind profiler radar according to claim 3, characterized in that S3 include: S31 obtains the wind speed and / or wind direction at each height of the vertical wind profile; S32. Calculate the height difference between adjacent heights, as well as the wind speed difference and / or wind direction difference; S33 calculates the rate of change of wind speed and / or wind direction with height, the rate of change WS1 is equal to the ratio of the wind speed difference to the height difference, the rate of change WS2 is equal to the ratio of the wind direction difference to the height difference; S34. Establish the fitting function of components u, v, and w with respect to height: u=a u0 +a u1 h+a u2 h 2 +a u3 h 3 +…+a un h n ; v=a v0 +a v1 h+a v2 h 2 +a v3 h 3 +…+a vn h n ; w=a w0 +a w1 h+a w2 h 2 +a w3 h 3 +…+a wn h n ; Among them, h is the height, α u0 ...α un , α v0 ...α vn , α w0 ...α wn is the resampling parameter, and n is the order of the fitting function; S35. Compare the change rate WS1 and / or the change rate WS2 with the preset threshold value to determine the order of the fitting function; when it is less than the preset threshold value, n=1; when it is equal to the preset threshold value, n=2; when it is greater than the preset threshold value, n=3; S36. Determine the resampling parameters using the least squares method; S37. Based on the determined order of the fitting function and the determined resampling parameter, obtain an adaptive fitting function of the components u, v, and w with respect to height; S38. Slice each wind profiler radar at any height, divide it into grids at the height, substitute the height of each grid into the fitting function of the adaptive components u, v, and w with respect to the height for resampling, and obtain the components of the wind speed vector at the same height.

5. The three-dimensional wind field construction method based on wind profiler radar according to claim 4 is characterized in that: The process of determining the resampling parameters using the least squares method in S36 is as follows: Obtain the height value of each layer of the vertical wind profile detected by each wind profile radar, form it into a matrix H according to formula 13, and the vectors of the components corresponding to the height are Their forms are as shown in Equation 14, Equation 15 and Equation 16; Formula 13: Formula 14: Formula 15: Formula 16: Where m is the height layer of the profile obtained by wind profiler radar detection; Then we can get the parameters of each fitting function and Such as formula 17, formula 18 and formula 19; Formula 17: Formula 18: Formula 19:

6. The three-dimensional wind field construction method based on wind profiler radar according to claim 5, characterized in that: In S4, the wind speed component fitting model is used to calculate the wind speed component values ​​of all horizontal grids at each height grid to complete the construction of the three-dimensional wind field; The fitting model of the wind speed component is: Where N is the number of wind profiler radars; u i (x i ,y i ,z)、v i (x i ,y i ,z)、w i (x i ,y i ,z) are the resampled values ​​of each wind profiler radar on the height grid z; x and y are the coordinates on each divided grid; x i and y i is the coordinate of each wind profiler radar on the horizontal grid; a i (x,y) is the weight of the estimated grid and each wind profiler radar.

7. The three-dimensional wind field construction method based on wind profiler radar according to claim 6, characterized in that: Use the following formula to determine the weight a i (x,y): Among them, x i and y i is the coordinate of each wind profiler radar on the horizontal plane, d i (x,y) is the distance between the estimated grid and each wind profiler radar.

8. A three-dimensional wind field construction system based on wind profiler radar, characterized in that: include: A data acquisition module, used to acquire wind profiler radar horizontal wind and vertical wind data of each wind profiler radar; A wind profile data determination module is used to determine the wind profile data of the corresponding position of each wind profile radar based on the horizontal wind and vertical wind data of the wind profile radar, specifically including: Establish a geocentric coordinate system; Determining a local coordinate system for the location of each wind profiler radar based on the geocentric coordinate system; The local coordinate system of one of the wind profiler radars is used as a reference coordinate system, and the local coordinate systems of the remaining wind profiler radars are converted to the reference coordinate system; After conversion, the wind speed vector of each wind profiler radar is corrected; A correction module is used to correct the wind speed vector on the vertical wind profile based on the wind profile data; an adaptive resampling module is used to adaptively resample the wind speed vector on the vertical wind profile after correction to obtain wind speed data at the same altitude layer; The three-dimensional wind field construction module is used to construct a three-dimensional wind field based on the wind speed data at the same altitude layer through a wind profile radar network and a distance-weighted method.

9. A computer-readable storage medium, characterized in that The storage medium stores computer instructions. When a computer reads the computer instructions, the computer executes the three-dimensional wind field construction method based on wind profiler radar according to any one of claims 1 to 7.

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