Wind speed map drawing method, device and system and storage medium

Abstract

The invention discloses a wind speed map drawing method, device and system and a storage medium, and the method comprises the steps: obtaining mesoscale meteorological data of a target region from a database used for recording meteorological data, and obtaining a topographic map of the target region; setting boundary layer parameters and boundary conditions for a topographic map of a target area based on the mesoscale meteorological data; performing CFD simulation on the target area according to the boundary layer parameters and the boundary conditions to obtain a simulated wind speed value of any point in the space of the target area; calculating a long-term wind speed sequence of any point in the target area space according to the simulated wind speed value and the wind speed in the mesoscale meteorological data; and drawing a wind speed map of the target area according to the long-term wind speed sequence. According to the method, the mesoscale meteorological data and the CFD simulation technology are deeply fused, the wind speed map of the target area can be obtained without arranging an anemometer tower in advance or performing long-term wind measurement, the wind speed measurement efficiency is improved, and the wind speed measurement and calculation cost is reduced.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of wind speed measurement, and in particular to a wind speed atlas drawing method, device, system and storage medium. BACKGROUND

[0002] With the rapid development of China's new energy industry, the installed capacity of wind power continues to rise. Under this background, wind resource assessment has become an indispensable part of wind power project approval and investment decision-making. The efficiency of wind speed calculation is directly related to the smoothness of project progress, while the accuracy of calculation plays a decisive role in the accuracy of wind farm yield prediction, and thus deeply affects the overall economic benefit and subsequent evaluation of the wind power project.

[0003] To achieve high reliability of micro-siting of wind farms, ten-meter fine resolution wind speed and other key meteorological parameters need to be captured within the planning area of the wind farm (generally ranging from 5 to 20 square kilometers). However, the output resolution (not less than 1 kilometer) of the currently widely used mesoscale meteorological model (such as WRF) cannot meet this fine requirement. Especially in areas with complex terrain and variable climate, the limited data accuracy of traditional wind resource assessment methods leads to large prediction deviation of power generation, affecting the accuracy of project feasibility study. This forces the project party to excessively rely on the wind measurement tower built in advance and at least one year of wind data collection, not only delaying the project progress, but also causing high pre-construction cost loss when the project is cancelled.

[0004] Therefore, how to provide a wind speed atlas drawing method to improve the efficiency of wind speed measurement and reduce the cost of wind speed calculation has become a technical problem to be solved. SUMMARY

[0005] The present application provides a wind speed atlas drawing method, device, system and storage medium to improve the efficiency of wind speed measurement and reduce the cost of wind speed calculation.

[0006] The present application provides a wind speed atlas drawing method, comprising:

[0007] Obtain mesoscale meteorological data of a target area from a database for recording meteorological data, and obtain a topographic map of the target area, wherein the target area includes a core calculation area and a peripheral buffer zone, and the topographic map of the target area contains height data of the target area;

[0008] Set boundary layer parameters and boundary conditions for the topographic map of the target area based on the mesoscale meteorological data;

[0009] Perform CFD simulation on the target area according to the boundary layer parameters and boundary conditions to obtain a simulated wind speed value of any point in the space of the target area, and the simulated wind speed value is related to the height.

[0010] calculating a long-term wind speed sequence of any point in the target region space according to the simulated wind speed value and the wind speed in the mesoscale meteorological data;

[0011] drawing a wind speed atlas of the target region according to the long-term wind speed sequence.

[0012] The application has the beneficial effects that: the mesoscale meteorological data of a target region is obtained from a database for recording meteorological data, and a topographic map of the target region is obtained, wherein the target region includes a core calculation area and a peripheral buffer zone, and the topographic map of the target region contains height data of the target region; boundary layer parameters and boundary conditions are set for the topographic map of the target region based on the mesoscale meteorological data; CFD simulation is performed on the target region according to the boundary layer parameters and boundary conditions to obtain a simulated wind speed value of any point in the target region space, and the simulated wind speed value is related to the height; a long-term wind speed sequence of any point in the target region space is calculated according to the simulated wind speed value and the wind speed in the mesoscale meteorological data; and a wind speed atlas of the target region is drawn according to the long-term wind speed sequence. Since the application deeply integrates mesoscale meteorological data and CFD simulation technology, it is not necessary to pre-arrange a wind measurement tower or perform long-term wind measurement, and the wind speed atlas of the target region can be obtained by accurately correcting the simulated boundary conditions with mesoscale data and combining CFD simulation measurement, thereby ensuring the accuracy of wind speed measurement, improving the efficiency of wind speed measurement, and reducing the cost of wind speed measurement.

[0013] In one embodiment, the topographic map of the target region contains height data of the target region, and the method comprises:

[0014] obtaining an SRTM3 topographic map of the target region;

[0015] converting the SRTM3 topographic map into a CGCS2000 coordinate system;

[0016] generating contour DEM topographic maps corresponding to a plurality of wind direction sectors according to the topographic map after coordinate conversion;

[0017] griding the DEM topographic maps corresponding to the plurality of wind direction sectors respectively to obtain the topographic map of the target region.

[0018] In one embodiment, the boundary layer parameters and boundary conditions are set for the topographic map of the target region based on the mesoscale meteorological data, and the method comprises:

[0019] obtaining a wind speed value at a preset height in the mesoscale meteorological data of the target region;

[0020] calculating a surface roughness and a friction velocity according to the wind speed value at the preset height.

[0021] calculating the inlet boundary wind speed according to the ground roughness, the friction velocity and the average ground elevation of the core calculation area;

[0022] setting the ground roughness, the friction velocity and the inlet boundary wind speed as boundary layer parameters and boundary conditions.

[0023] In one embodiment, the preset height wind speed values include the average wind speed at 10 meters height and the average wind speed at 100 meters height, and the calculating the ground roughness and the friction velocity according to the preset height wind speed values comprises:

[0024] substituting the preset height wind speed values into the following first formula to calculate the ground roughness:

[0025]

[0026] wherein z 0-1 is the ground roughness; U 10ave-1 is the average wind speed at 10 meters height; U 100ave-1 is the average wind speed at 100 meters height;

[0027] substituting the ground roughness and the preset height wind speed values into the following second formula to calculate the friction velocity:

[0028]

[0029] wherein μ *-1 is the friction velocity; k * is the Karman constant; U 100ave-1 is the average wind speed at 100 meters height; z 0-1 is the ground roughness.

[0030] In one embodiment, the calculating the inlet boundary wind speed according to the ground roughness, the friction velocity and the average ground elevation of the core calculation area comprises:

[0031] obtaining the average ground elevation of each grid point in the core calculation area;

[0032] calculating the average ground elevation of the core calculation area according to the average ground elevation of each grid point in the core calculation area;

[0033] calculating the inlet boundary wind speed according to the ground roughness, the friction velocity and the average ground elevation of the core calculation area.

[0034] In one embodiment, the calculating the long-term wind speed sequence of any point in the target area space according to the simulated wind speed values and the wind speed in the mesoscale meteorological data comprises:

[0035] a wind acceleration factor is calculated according to the simulated wind speed value of any point in the target region space and the wind speed value of a preset height corresponding to the mesoscale meteorological data;

[0036] a long-term wind speed sequence of the target region space is obtained by correcting the long-term wind speed sequence of the preset height in the mesoscale meteorological data using the wind acceleration factor.

[0037] In one embodiment, the mesoscale meteorological data is divided into multiple sectors, each sector corresponding to a different wind direction range, and the wind speed atlas of the target region is drawn according to the long-term wind speed sequence, comprising:

[0038] obtaining a long-term wind speed sequence of all sectors corresponding to any point in the target region space;

[0039] calculating the full-sector average wind speed of any point in the target region space according to the long-term wind speed sequence of all sectors corresponding to any point in the target region space;

[0040] drawing the wind speed atlas of the target region according to the full-sector average wind speed of all points in the target region space.

[0041] The application also provides a wind speed atlas drawing device, comprising:

[0042] an acquisition module for acquiring mesoscale meteorological data of a target region from a database for recording meteorological data and acquiring a topographic map of the target region, wherein the target region comprises a core calculation area and a peripheral buffer zone, and the topographic map of the target region contains height data of the target region;

[0043] a setting module for setting boundary layer parameters and boundary conditions for the topographic map of the target region based on the mesoscale meteorological data;

[0044] a simulation module for CFD simulation of the target region according to the boundary layer parameters and boundary conditions to obtain a simulated wind speed value of any point in the target region space, the simulated wind speed value being related to height;

[0045] a calculation module for calculating a long-term wind speed sequence of any point in the target region space according to the simulated wind speed value and the wind speed in the mesoscale meteorological data;

[0046] a drawing module for drawing a wind speed atlas of the target region according to the long-term wind speed sequence.

[0047] In one embodiment, the acquisition module comprises:

[0048] a first acquisition submodule for acquiring an SRTM3 topographic map of the target region;

[0049] a conversion module, configured to convert the SRTM3 terrain map into a CGCS2000 coordinate system;

[0050] a generation module, configured to generate a plurality of wind direction sector corresponding contour DEM terrain maps according to the terrain map after coordinate conversion;

[0051] a gridding module, configured to grid the DEM terrain maps corresponding to the plurality of wind direction sectors respectively to obtain the terrain map of the target area.

[0052] In an embodiment, the setting module comprises:

[0053] a second acquisition module, configured to acquire a wind speed value at a preset height in mesoscale meteorological data of a target area;

[0054] a first calculation module, configured to calculate a surface roughness and a friction velocity according to the wind speed value at the preset height;

[0055] a second calculation module, configured to calculate an inlet boundary wind speed according to the surface roughness, the friction velocity and a ground average elevation of a core calculation area;

[0056] a setting module, configured to set the surface roughness, the friction velocity and the inlet boundary wind speed as a boundary layer parameter and a boundary condition.

[0057] In an embodiment, the wind speed value at the preset height comprises an average wind speed at a height of 10 meters and an average wind speed at a height of 100 meters, and the first calculation module is further configured to:

[0058] substitute the wind speed value at the preset height into a first formula as follows to calculate the surface roughness:

[0059]

[0060] wherein z 0-1 is the surface roughness; U 10ave-1 is the average wind speed at the height of 10 meters; U 100ave-1 is the average wind speed at the height of 100 meters.

[0061] substitute the surface roughness and the wind speed value at the preset height into a second formula as follows to calculate the friction velocity:

[0062]

[0063] wherein μ *-1 is the friction velocity; k * is a Karman constant; U 100ave-1 is the average wind speed at the height of 100 meters; z0-1 a surface roughness.

[0064] In one embodiment, the second calculation submodule is further configured to:

[0065] obtain average elevations of each grid point on the ground in the core calculation area;

[0066] calculate an average elevation of the ground in the core calculation area according to the average elevations of each grid point on the ground in the core calculation area;

[0067] calculate the inlet boundary wind speed according to the surface roughness, the friction velocity, and the average elevation of the ground in the core calculation area.

[0068] In one embodiment, the calculation module comprises:

[0069] a third calculation submodule configured to calculate a wind acceleration factor according to a simulated wind speed value of an arbitrary point in the target area space and a wind speed value at a preset height in the mesoscale meteorological data;

[0070] a correction submodule configured to correct a long-term wind speed sequence at the preset height in the mesoscale meteorological data by using the wind acceleration factor to obtain a long-term wind speed sequence of the arbitrary point in the target area space.

[0071] In one embodiment, the mesoscale meteorological data is divided into a plurality of sectors, each sector corresponding to a different wind direction range, and the drawing module comprises:

[0072] a third acquisition submodule configured to acquire a long-term wind speed sequence of all sectors corresponding to the arbitrary point in the target area space;

[0073] a fourth calculation submodule configured to calculate a full-sector average wind speed of the arbitrary point in the target area space according to the long-term wind speed sequence of all sectors corresponding to the arbitrary point in the target area space;

[0074] a drawing submodule configured to draw a wind speed atlas of the target area according to the full-sector average wind speeds of all points in the target area space.

[0075] The application also provides a wind speed atlas drawing system, comprising:

[0076] at least one processor; and

[0077] a memory in communication connection with the at least one processor; wherein

[0078] the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the wind speed atlas drawing method described in any of the above embodiments.

[0079] The application further provides a computer readable storage medium, when instructions in the storage medium are executed by a processor corresponding to a wind speed atlas drawing system, the wind speed atlas drawing system can implement the wind speed atlas drawing method described in any of the embodiments.

[0080] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent from the description, or can be learned by practice of the present application. The objects and other advantages of the present application will be realized and attained by means of the instrumentalities particularly pointed out in the written description and claims hereof as well as the appended drawings.

[0081] The technical solutions of the present application will be described in further detail below with the help of the accompanying drawings and embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0082] The accompanying drawings are included to provide a further understanding of the present application, and constitute a part of the specification, illustrate embodiments of the present application, and are used to explain the present application together with the written description. The drawings are not intended to limit the present application, and in the drawings:

[0083] Figure 1 Flow chart of a wind speed atlas drawing method in an embodiment of the present application;

[0084] Figure 2 Target area topographic map in an embodiment of the present application;

[0085] Figure 3 Sectorized topographic map schematic diagram in an embodiment of the present application;

[0086] Figure 4 Comparison effect diagram of core calculation area and buffer area grid division in an embodiment of the present application;

[0087] Figure 5 Encryption effect diagram of core calculation area grid division in an embodiment of the present application;

[0088] Figure 6 Boundary layer schematic diagram in an embodiment of the present application;

[0089] Figure 7 Schematic diagram of a wind speed atlas in an embodiment of the present application;

[0090] Figure 8 Structural schematic diagram of a wind speed atlas drawing device in an embodiment of the present application;

[0091] Figure 9 Hardware structural schematic diagram of a wind speed atlas drawing system in an embodiment of the present application. DETAILED DESCRIPTION

[0092] The preferred embodiments of the present application are described below in conjunction with the accompanying drawings, in which it is understood that the preferred embodiments described below are merely used to illustrate and explain the present application, and are not used to limit the present application.

[0093] The method provided by the present application does not need to arrange a wind measurement tower and long-period wind measurement, and through key technologies such as boundary condition correction by mesoscale data and multi-level grid self-adaptive optimization, the efficiency and accuracy of wind speed measurement under various terrains are significantly improved, a convenient and reliable simulation and measurement tool is provided for the wind resource evaluation link in the strategic decision of a wind power project development, and the early-stage cost is saved in the pre-feasibility study stage of the project.

[0094] Figure 1 For a flowchart of a wind speed atlas drawing method in an embodiment of the present application, as shown in Figure 1 The method can be implemented as the following steps S101-S105:

[0095] In step S101, mesoscale meteorological data of a target area is obtained from a database for recording meteorological data, and a topographic map of the target area is obtained, wherein the target area includes a core calculation area and a peripheral buffer zone, and the topographic map of the target area contains height data of the target area;

[0096] In step S102, boundary layer parameters and boundary conditions are set for the topographic map of the target area based on the mesoscale meteorological data;

[0097] In step S103, CFD simulation is performed on the target area according to the boundary layer parameters and boundary conditions to obtain a simulated wind speed value of any point in the space of the target area, and the simulated wind speed value is related to the height;

[0098] In step S104, a long-term wind speed sequence of any point in the space of the target area is calculated according to the simulated wind speed value and the wind speed in the mesoscale meteorological data;

[0099] In step S105, a wind speed atlas of the target area is drawn according to the long-term wind speed sequence.

[0100] In the present application, mesoscale meteorological data of a target area is obtained from a database for recording meteorological data, and a topographic map of the target area is obtained, wherein the target area includes a core calculation area and a peripheral buffer zone, and the topographic map of the target area contains height data of the target area.

[0101] Specifically, the mesoscale meteorological data of the target area is obtained as the macroscopic meteorological background field of the CFD inlet. The meteorological data includes but is not limited to ERA5, MERRA2 or Chinese meteorological mesoscale data. Taking ERA5 as an example, the global meteorological database (ERA5) is the most advanced global atmospheric reanalysis dataset at present, which provides hourly meteorological data from 1940 to now, covering global atmospheric, terrestrial and marine variables. Its spatio-temporal continuity and parameter integrity can provide basic input for wind farm flow field simulation, and provide large-scale, mesoscale meteorological data field for initial and boundary conditions of CFD simulation. These data cover meteorological elements in a larger range (such as hundreds to thousands of kilometers), including but not limited to wind speed, wind direction, temperature, air pressure, humidity, etc. The macroscopic meteorological background field mainly provides the initial value and boundary condition of the key meteorological parameters such as wind speed and wind direction for CFD simulation.

[0102] In the present application, the target area includes a core calculation area and a peripheral buffer area, for example, the rectangular area with the longitude (110.875, 111.125) and the latitude (41.875, 42.125) as the core calculation area, and the peripheral buffer area refers to the additional simulation area extended around the core calculation area to minimize the influence of the initial flow disturbed by the sudden terrain. Figure 2 For the topographic map of the target area in an embodiment of the present application, as shown in Figure 2 The target area contains the core calculation area and the peripheral buffer area. The selection of the peripheral buffer area can approximate the core calculation area to a rectangle, and the circumscribed circle radius of the rectangle is calculated and a square area with 2*R as the side length is drawn. The part of the square area outside the core calculation area is the peripheral buffer area.

[0103] In order to analyze the wind speed of any point in the target area, the topographic map of the target area is obtained, which contains the height data of the target area. Therefore, the SRTM3 (Shuttle Radar Topography Mission) topographic map of the target area is obtained, wherein the SRTM3 is a global terrain elevation dataset with a terrain resolution of 30 meters. The SRTM3 topographic map of the target area is obtained, for example, for the aforementioned target area, the geographic range is also east longitude (110.875, 111.125) and north latitude (41.875, 42.125), and this area is taken as the core calculation area of the CFD model. Since the SRTM3 is in the WGS84 coordinate system, it is necessary to convert the SRTM3 topographic map to the CGCS2000 coordinate system (the legal geodetic coordinate system in China) to avoid plane error and elevation distortion after CFD terrain input. For example, the 111° central meridian and the Gauss 3° zone are selected as parameters, and ellipsoid transformation is realized through translation, rotation and scale factor. Then, according to the topographic map after coordinate conversion, a plurality of wind direction sector corresponding contour DEM (Digital Elevation Model) topographic maps are generated, wherein the DEM topographic map includes the core calculation area and the peripheral buffer area. In the actual application in the wind resource assessment, the wind farm will usually divide the sectors according to the wind direction frequency, and each sector corresponds to a different wind direction range. In this way, the wind energy resources in each direction can be more accurately analyzed. Therefore, when processing the topographic map, it is necessary to divide it according to different sectors, and the core calculation area does not need to be changed, only the peripheral buffer area needs to be rotated to adapt to the input of the CFD simulation entrance boundary. Table 1 is the sector information of the sectorized topography in an embodiment of the present application, Figure 3 Corresponding to Table 1, Figure 3 is a schematic diagram of the sectorized topographic map in an embodiment of the present application. Since the entrance wind direction is directly changed, too many parameters need to be changed, and the present application directly changes the direction of the peripheral buffer area, and rotates it by 22.5 degrees each time, as shown in Table 1 and Figure 3 In order to determine the wind speed of each point in the core calculation area under different wind directions, the topographic map is divided into 16 sectors in the present embodiment, corresponding to 16 wind directions.

[0104] Table 1 Sector information of sectorized topography

[0105]

[0106] Afterwards, the DEM topographic map corresponding to each wind direction sector is gridded to obtain a preprocessed topographic map. Gridding defines the conversion of discrete DEM elevation sampling points into elevation matrix data of regular grid structure through mathematical interpolation algorithm, each grid cell stores an elevation value, to generate a structured terrain surface model. In actual execution, the number of grid points needs to be determined comprehensively in combination with the degree of terrain undulation (such as mountainous areas requiring finer grids), mapping objectives and accuracy requirements. In this application, in order to capture the characteristics of the ground model, the 16 sectors are divided into grids in an unstructured manner, high-precision grids are selected for the core calculation area, and low-precision grids are selected for the peripheral buffer zone. Taking the "North" sector as an example, Figure 4 is a comparison effect diagram of the grid division of the core calculation area and the buffer area in an embodiment of the present application, Figure 5 is an encryption effect diagram of the grid division of the core calculation area in an embodiment of the present application, as shown in Figure 4 and Figure 5 , 20m precision grids are used for the core calculation area, matching the 30m resolution of SRTM3 terrain data, which ensures the calculation accuracy while reducing the spatial scale, and 100m precision grids are used for the peripheral buffer zone, balancing the calculation efficiency through unstructured division.

[0107] Boundary layer parameters and boundary conditions are set for the topographic map of the target area based on the mesoscale meteorological data.

[0108] The setting of the boundary layer is particularly important on the basis of the spatial grid, because the generation and dissipation of the near-surface turbulence is very intensive, Figure 6 is a schematic diagram of the boundary layer in an embodiment of the present application, as shown in Figure 6 , the first layer boundary layer height is 4m in an embodiment of the present application. When setting the boundary conditions, taking the "North" sector as an example, the north direction is the inlet boundary, the south direction is the outlet boundary, the ground is the wall boundary, the east and west directions are the symmetric boundary, and the top is the slip boundary, which are written into the k, epsilon, p, U parameter dictionaries respectively. Since the wind profile model is a mathematical expression describing the change of wind speed with height in the atmospheric boundary layer, the inlet wind speed can be set by using the wind profile model. First, the wind speed values at the preset height in the target area are obtained, taking the "North" sector as an example, the average wind speeds U 10ave-1 and U 100ave-1 at the heights of 10m and 100m in the range of 348.75-11.25 degrees in ERA5 are obtained. A more reasonable wind profile is generated by the wind speed at different heights, which increases the accuracy of CFD simulation as the setting of the inlet boundary condition. Then, the surface roughness and friction velocity are calculated according to the wind speed values at the preset height. According to the logarithmic wind profile law under neutral atmospheric conditions, the formulas for the change of wind speed with height are respectively:

[0109]

[0110] wherein U 10ave-1 is the average wind speed at 10 meters height; U 100ave-1 is the average wind speed at 100 meters height; μ *-1 is the friction velocity; k * is the Karman constant, which is taken as 0.41; z 0-1 is the surface roughness.

[0111] The above two equations can be eliminated By solving the equation, we have: The surface roughness is obtained as:

[0112]

[0113] The friction velocity can also be obtained as:

[0114]

[0115] Further, the average elevation of the ground in the core calculation area is obtained. Specifically, the coordinates P Wp (x Wp , y Wp , z Wp ) of each grid point of the ground in the core calculation area are obtained, and the z-axis coordinates (i.e., the elevation) of all grid points of the ground are calculated as an arithmetic mean to obtain the average elevation of the ground. That is, the average elevation of the ground is obtained according to the following formula:

[0116]

[0117] wherein H ave is the average elevation of the ground in the core calculation area; z wp is the elevation of the grid point in the core calculation area; and p is the number of grid points in the core calculation area.

[0118] The wind speed of any point P Bq-1 (x Bq-1 , y Bq-1 , z Bq-1 ) on the inlet boundary is calculated as:

[0119]

[0120] wherein U Bq-1 is the wind speed of any point P Bq-1 on the inlet boundary; μ *-1 is the friction velocity; k * is the Karman constant; z Bq-1 is the elevation of the point P Bq-1 ; H ave is the average elevation of the ground in the core calculation area; and z 0-1to determine a surface roughness.

[0121] Finally, the surface roughness, the friction velocity and the inlet boundary wind speed are set as boundary layer parameters and boundary conditions.

[0122] CFD simulation is performed on the target area according to the boundary layer parameters and boundary conditions to obtain a simulated wind speed value of any point in the target area space, which is related to the height. Specifically, the target area can be simulated by using OpenFOAM software according to the boundary layer parameters and boundary conditions to obtain the simulated wind speed value of any point in the space. For example, the flow field data can be obtained by solving the NS equation. In an embodiment of the present application, the RANS method is used in the solving process, which is fast in calculation efficiency and widely used. The NS equation (Navier-Stokes equation) is a set of nonlinear partial differential equations describing the motion of viscous fluid, which is derived based on Newton's second law and covers momentum and mass conservation, and is widely used in fluid mechanics and engineering fields. RANS (Reynolds-averaged Navier-Stokes equation) is a core method for simulating turbulent flow in computational fluid dynamics (CFD), which describes the statistical properties of turbulent flow by time-averaging the Navier-Stokes equation. After the calculation converges, the simulated flow field results can be obtained, in which the simulated wind speed value of any point P n (x n , y n , z n ) is (V nx-1 and V ny-1 are the wind speed components of P n point in the horizontal x and y directions).

[0123] A long-term wind speed sequence of any point in the target area space is calculated according to the simulated wind speed value and the wind speed in the mesoscale meteorological data. First, a wind acceleration factor is calculated according to the simulated wind speed value of any point in the target area space and the wind speed value at the corresponding preset height in the mesoscale meteorological data. Specifically, the simulated wind speed value of any point in the target area space and the wind speed value at the corresponding preset height in the mesoscale meteorological data are substituted into the following formula to determine the wind acceleration factor of any point:

[0124] K n-1 = V n-1 / U 100ave-1 ;

[0125] wherein K n-1 is the wind acceleration factor; V n-1 is the wind speed; and U 100ave-1 is the average wind speed at 100 meters high.

[0126] Then, the long-term wind speed sequence at a preset height in the mesoscale meteorological data is corrected using the wind acceleration factor to obtain the long-term wind speed sequence at any point within the target area. For example, the wind speed data at all 100m heights within this sector for ERA5 are obtained. By correcting for the wind acceleration factor, the corrected long-term series wind speed at any point can be obtained.

[0127] Finally, a wind speed map of the target area is plotted based on the long-term wind speed series. Since wind direction varies significantly over time (e.g., seasonally or diurnalally), data from a single moment cannot represent the long-term wind energy potential; the wind speed across the entire sector is quantified by statistically analyzing the average wind speed or probability distribution across 16 azimuth angles to quantify the energy contribution from different directions. Therefore, the process for the remaining 15 sectors is repeated with the "North" sector to obtain hourly wind speed data for all sectors over 20 years, with a spatial scale of 20m, achieving a micro-level site selection assessment. The average wind speed of the entire sector at any point within the target area is calculated based on the long-term time-series wind speed data; a wind speed map of the target area is then plotted based on the average wind speed of the entire sector at any point.

[0128] Specifically, for any point P in space n (x n y n , z n To obtain the average wind speed across the entire sector:

[0129]

[0130] To plot wind speed maps at any altitude, such as 100 meters, you can add 100 to the z-axis coordinates of the ground grid points to obtain the coordinates of the corresponding points, i.e., P. Wp (x Wp y Wp , z Wp +100), and then calculate the average wind speed at all points, plot the map, which can provide a visual basis for wind resource assessment. For example... Figure 7 As shown, Figure 7 This is a schematic diagram of a wind speed map according to one embodiment of this application.

[0131] The method provided in this application enables rapid and high-precision calculation of project wind speed even without measured wind speed data or topographic maps; it allows for downscaling studies, reducing wind speed data to the ten-meter level using mesoscale data, which can then be applied to wind turbine site selection; it provides important theoretical basis for wind power project site selection and investment decisions; it reduces procurement processes and saves on upfront costs such as erecting wind measurement towers during the pre-feasibility study stage; it saves the time cost of at least one year required for wind speed data collection by wind measurement towers, improving project efficiency; and it promotes industry standard advancement, leading to changes in wind speed collection standards during the project feasibility study stage after industry recognition and promotion, thus saving project investment and construction costs.

[0132] The application has the beneficial effect that: the mesoscale meteorological data of a target area is obtained from a database for recording meteorological data, and a topographic map of the target area is obtained, wherein the target area includes a core calculation area and a peripheral buffer zone, and the topographic map of the target area contains height data of the target area; boundary layer parameters and boundary conditions are set for the topographic map of the target area based on the mesoscale meteorological data; the target area is simulated by CFD according to the boundary layer parameters and boundary conditions to obtain a simulated wind speed value of any point in the target area space, and the simulated wind speed value is related to the height; a long-term wind speed sequence of any point in the target area space is calculated according to the simulated wind speed value and the wind speed in the mesoscale meteorological data; and a wind speed atlas of the target area is drawn according to the long-term wind speed sequence. Since the application deeply integrates mesoscale meteorological data and CFD simulation technology, it is not necessary to pre-arrange a wind measurement tower or perform long-term wind measurement, and the wind speed atlas of the target area can be obtained by accurately correcting the simulation boundary conditions with mesoscale data and combining CFD simulation measurement, which ensures the accuracy of wind speed measurement while improving the efficiency of wind speed measurement and reducing the cost of wind speed measurement.

[0133] In one embodiment, the above-mentioned step S101 of obtaining the topographic map of the target area can be implemented as steps A1-A4 as follows:

[0134] In step A1, an SRTM3 topographic map of the target area is obtained;

[0135] In step A2, the SRTM3 topographic map is converted into a CGCS2000 coordinate system;

[0136] In step A3, a plurality of wind direction sector corresponding contour DEM topographic maps are respectively generated according to the topographic map after coordinate conversion;

[0137] In step A4, the DEM topographic maps corresponding to the plurality of wind direction sectors are respectively gridded to obtain the topographic map of the target area.

[0138] In one embodiment, the above-mentioned step S102 can be implemented as steps B1-B4 as follows:

[0139] In step B1, the wind speed value at a preset height in the mesoscale meteorological data of the target area is obtained;

[0140] In step B2, the surface roughness and friction velocity are calculated according to the wind speed value at the preset height;

[0141] In step B3, the inlet boundary wind speed is calculated according to the surface roughness, friction velocity and average ground elevation of the core calculation area;

[0142] In step B4, the ground roughness, the friction velocity and the inlet boundary wind speed are set as boundary layer parameters and boundary conditions according to the ground roughness, the friction velocity and the inlet boundary wind speed.

[0143] In one embodiment, the preset height wind speed values include a 10-meter height average wind speed and a 100-meter height average wind speed, and the step B2 can be implemented as steps B21-B22 as follows:

[0144] In step B21, the preset height wind speed values are substituted into a first formula as follows to calculate the ground roughness:

[0145]

[0146] wherein z 0-1 is the ground roughness; U 10ave-1 is the 10-meter height average wind speed; and U 100ave-1 is the 100-meter height average wind speed.

[0147] In step B22, the ground roughness and the preset height wind speed values are substituted into a second formula as follows to calculate the friction velocity:

[0148]

[0149] wherein μ *-1 is the friction velocity; k * is the Karman constant; U 100ave-1 is the 100-meter height average wind speed; and z 0-1 is the ground roughness.

[0150] In one embodiment, the step B3 can be implemented as steps B31-B33 as follows:

[0151] In step B31, the average elevations of the grid points on the ground in the core calculation area are obtained;

[0152] In step B32, the average elevation of the ground in the core calculation area is calculated according to the average elevations of the grid points on the ground in the core calculation area;

[0153] In step B33, the inlet boundary wind speed is calculated according to the ground roughness, the friction velocity and the average elevation of the ground in the core calculation area.

[0154] In one embodiment, the step S104 can be implemented as steps C1-C2 as follows:

[0155] In step C1, the wind acceleration factor is calculated according to the simulation wind speed value of any point in the target area space and the preset height wind speed value corresponding to the mesoscale meteorological data;

[0156] In step C2, the long-term wind speed sequence of a preset height in the mesoscale meteorological data is corrected by using the wind acceleration factor to obtain a long-term wind speed sequence of any point in the target region space.

[0157] In one embodiment, the above step S105 can be implemented as steps D1-D3 as follows:

[0158] In step D1, a long-term wind speed sequence of all sectors corresponding to any point in the target region space is obtained.

[0159] In step D2, the full-sector average wind speed of any point in the target region space is calculated according to the long-term wind speed sequence of all sectors corresponding to the point in the target region space.

[0160] In step D3, a wind speed atlas of the target region is drawn according to the full-sector average wind speed of all points in the target region space.

[0161] Figure 8 An embodiment of a wind speed atlas drawing device is shown in the structure diagram as Figure 8 The device includes:

[0162] The acquisition module 801 is configured to acquire mesoscale meteorological data of a target region from a database for recording meteorological data and acquire a topographic map of the target region, wherein the target region includes a core calculation area and a peripheral buffer zone, and the topographic map of the target region contains height data of the target region.

[0163] The setting module 802 is configured to set a boundary layer parameter and a boundary condition for the topographic map of the target region based on the mesoscale meteorological data.

[0164] The simulation module 803 is configured to perform CFD simulation on the target region according to the boundary layer parameter and the boundary condition to obtain a simulated wind speed value of any point in the target region space, wherein the simulated wind speed value is related to the height.

[0165] The calculation module 804 is configured to calculate a long-term wind speed sequence of any point in the target region space according to the simulated wind speed value and a wind speed in the mesoscale meteorological data.

[0166] The drawing module 805 is configured to draw a wind speed atlas of the target region according to the long-term wind speed sequence.

[0167] In one embodiment, the acquisition module includes:

[0168] The first acquisition submodule is configured to acquire an SRTM3 topographic map of the target region.

[0169] A conversion module is configured to convert the SRTM3 terrain map into a CGCS2000 coordinate system;

[0170] A generation module is configured to generate a plurality of wind direction sector corresponding contour DEM terrain maps according to the terrain map after coordinate conversion;

[0171] A gridding module is configured to grid the DEM terrain maps corresponding to the plurality of wind direction sectors respectively to obtain the terrain map of the target area.

[0172] In one embodiment, the setting module comprises:

[0173] A second acquisition module is configured to acquire a wind speed value at a preset height in mesoscale meteorological data of a target area;

[0174] A first calculation module is configured to calculate a surface roughness and a friction velocity according to the wind speed value at the preset height;

[0175] A second calculation module is configured to calculate an inlet boundary wind speed according to the surface roughness, the friction velocity and a ground average elevation of a core calculation area;

[0176] A setting module is configured to set the surface roughness, the friction velocity and the inlet boundary wind speed as a boundary layer parameter and a boundary condition.

[0177] In one embodiment, the wind speed value at the preset height comprises an average wind speed at a height of 10 meters and an average wind speed at a height of 100 meters, and the first calculation module is further configured to:

[0178] Substitute the wind speed value at the preset height into a first formula as follows to calculate the surface roughness:

[0179]

[0180] wherein z 0-1 is the surface roughness; U 10ave-1 is the average wind speed at the height of 10 meters; U 100ave-1 is the average wind speed at the height of 100 meters.

[0181] Substitute the surface roughness and the wind speed value at the preset height into a second formula as follows to calculate the friction velocity:

[0182]

[0183] wherein μ *-1 is the friction velocity; k * is the Karman constant; U 100ave-1 is the average wind speed at the height of 100 meters; z 0-1 is the surface roughness.

[0184] In one embodiment, the second calculation submodule is further configured to:

[0185] obtain average elevations of each grid point on the ground surface in the core calculation area;

[0186] calculate an average elevation of the ground surface in the core calculation area according to the average elevations of each grid point on the ground surface in the core calculation area;

[0187] calculate the inlet boundary wind speed according to the surface roughness, the friction velocity, and the average elevation of the ground surface in the core calculation area.

[0188] In one embodiment, the calculation module comprises:

[0189] a third calculation submodule configured to calculate a wind acceleration factor according to a simulated wind speed value of an arbitrary point in the target area space and a wind speed value at a preset height in the mesoscale meteorological data;

[0190] a correction submodule configured to correct a long-term wind speed sequence at the preset height in the mesoscale meteorological data by using the wind acceleration factor, to obtain a long-term wind speed sequence of the arbitrary point in the target area space.

[0191] In one embodiment, the mesoscale meteorological data is divided into a plurality of sectors, each sector corresponding to a different wind direction range, and the drawing module comprises:

[0192] a third acquisition submodule configured to acquire a long-term wind speed sequence of all sectors corresponding to the arbitrary point in the target area space;

[0193] a fourth calculation submodule configured to calculate a full-sector average wind speed of the arbitrary point in the target area space according to the long-term wind speed sequences of all sectors corresponding to the arbitrary point in the target area space;

[0194] a drawing submodule configured to draw a wind speed atlas of the target area according to the full-sector average wind speeds of all points in the target area space.

[0195] Figure 9 FIG. 1 shows a hardware structure diagram of a wind speed atlas drawing system according to an embodiment of the present application. Figure 9 The wind speed atlas drawing system comprises:

[0196] at least one processor 920; and

[0197] a memory 904 in communication connection with the at least one processor 920; wherein

[0198] The memory 904 stores instructions that are executable by the at least one processor 920, and the instructions are executed by the at least one processor 920 to implement the wind speed mapping method described in any of the above embodiments.

[0199] Referring to Figure 9 The wind speed mapping system 900 can include one or more of the following components: a processing component 902, a memory 904, a power supply component 906, a multimedia component 908, an audio component 910, an input / output (I / O) interface 912, a sensor component 914, and a communication component 916.

[0200] The processing component 902 usually controls overall operations of the wind speed mapping system 900. The processing component 902 can include one or more processors 920 to execute instructions to complete all or part of steps of the methods described above. In addition, the processing component 902 can include one or more modules to facilitate the interaction between the processing component 902 and other components. For example, the processing component 902 can include a multimedia module to facilitate the interaction between the multimedia component 908 and the processing component 902.

[0201] The memory 904 is configured to store various types of data to support the operation of the wind speed mapping system 900. Examples of these data include instructions for any application or method operating on the wind speed mapping system 900, such as text, pictures, videos, etc. The memory 904 can be implemented by any type of volatile or non-volatile storage devices or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0202] The power supply component 906 provides power for various components of the wind speed mapping system 900. The power supply component 906 can include a power supply management system, one or more power supplies, and other components associated with generating, managing and distributing power for the wind speed mapping system 900.

[0203] The multimedia component 908 includes a screen providing an output interface between the wind speed mapping system 900 and a user. In some embodiments, the screen can include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touch, swiping, and gestures on the touch panel. The touch sensor can not only sense a boundary of a touching or swiping action, but also detect duration and pressure related to the touching or swiping action. In some embodiments, the multimedia component 908 can further include a front camera and / or a rear camera. When the wind speed mapping system 900 is in an operation mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front camera and the rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0204] The audio component 910 is configured to output and / or input audio signals. For example, the audio component 910 includes a microphone (MIC) that is configured to receive external audio signals when the wind speed mapping system 900 is in an operation mode, such as an alarm mode, a recording mode, a voice recognition mode, and a voice output mode. The received audio signals can be further stored in the memory 904 or transmitted via the communication component 916. In some embodiments, the audio component 910 further includes a speaker for outputting audio signals.

[0205] The I / O interface 912 provides an interface between the processing component 902 and peripheral interface modules, which can be a keyboard, a click wheel, a button, and the like. The buttons can include, but are not limited to, a home button, a volume button, a start button, and a lock button.

[0206] The sensor component 914 includes one or more sensors for providing status assessment of various aspects of the wind speed mapping system 900. For example, the sensor component 914 can include a sound sensor. In addition, the sensor component 914 can detect the open / close status of the wind speed mapping system 900, the relative positioning of components, such as the display and keypad of the wind speed mapping system 900, the sensor component 914 can also detect the operational status of the wind speed mapping system 900 or a component of the wind speed mapping system 900, such as the operational status of the air distribution plate, the structural status, the operational status of the material discharge blade, etc., the orientation or acceleration / deceleration of the wind speed mapping system 900, and the temperature change of the wind speed mapping system 900. The sensor component 914 can include a proximity sensor configured to detect the presence of a nearby object without any physical contact. The sensor component 914 can also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor component 914 can also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, a material pile thickness sensor, or a temperature sensor.

[0207] The communication component 916 is configured to enable the wind speed mapping system 900 to provide wired or wireless communication capability with other devices and cloud platforms. The wind speed mapping system 900 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an example embodiment, the communication component 916 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In an example embodiment, the communication component 916 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0208] In an example embodiment, the wind speed mapping system 900 can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic elements for executing the wind speed mapping method described in any of the above embodiments.

[0209] The present application also provides a computer-readable storage medium, when the instructions in the storage medium are executed by the processor corresponding to the wind speed mapping system, the wind speed mapping system can implement the wind speed mapping method described in any of the above embodiments.

[0210] Those skilled in the art will appreciate that embodiments of the present application can be readily used as software, hardware, or a combination of software and hardware. In one embodiment, the present application can be implemented in software and can be stored on a computer readable medium, which can include random access memory (RAM), read only memory (ROM), magnetic disk or optical disk, or the like. The software implementation of the present application files can further be transmitted or received over a modem or network connection.

[0211] The embodiments of methods, apparatuses (systems) and computer program products according to the present application can be described below with reference to flowcharts and / or block diagrams illustrating the principle of the present application. It is understood by those skilled in the art that each flow and / or block in the flowcharts and / or block diagrams, as well as a combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, a special purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions, which are executed via the processor of the computer or other programmable data processing apparatus, generate a device implemented in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that performs the functions specified in the flow(s) or block(s).

[0212] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including instruction apparatus, which implements the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that performs the functions specified in the flow(s) or block(s).

[0213] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a process for implementing the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 an apparatus that performs the functions specified in the flow(s) or block(s).

[0214] It is obvious that those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for plotting wind speed maps, characterized in that, include: Mesoscale meteorological data of the target area are obtained from a database used to record meteorological data, and a topographic map of the target area is obtained. The target area includes a core computing area and an outer buffer zone, and the topographic map of the target area contains the elevation data of the target area. Based on the mesoscale meteorological data, boundary layer parameters and boundary conditions are set for the topographic map of the target area; CFD simulation is performed on the target area based on the boundary layer parameters and boundary conditions to obtain the simulated wind speed value at any point in the target area space. The magnitude of the simulated wind speed value is related to the height. Calculate the long-term wind speed sequence at any point in the target area based on the simulated wind speed value and the wind speed in the mesoscale meteorological data; Wind speed maps of the target area are plotted based on the long-term wind speed sequence.

2. The method as described in claim 1, characterized in that, The step of acquiring a topographic map of the target area, wherein the topographic map of the target area contains elevation data of the target area, includes: Obtain SRTM3 topographic maps of the target area; Convert the SRTM3 topographic map to the CGCS2000 coordinate system; Based on the topographic map after coordinate transformation, generate contour DEM topographic maps corresponding to multiple wind direction sectors; The DEM topographic maps corresponding to the multiple wind direction sectors are respectively gridded to obtain the topographic map of the target area.

3. The method as described in claim 1, characterized in that, The step of setting boundary layer parameters and boundary conditions for the topographic map of the target area based on the mesoscale meteorological data includes: Obtain wind speed values ​​at a preset altitude from mesoscale meteorological data of the target area; Calculate the surface roughness and friction speed based on the wind speed value at the preset height; The inlet boundary wind speed is calculated based on the surface roughness, friction speed, and average elevation of the core calculation area. The surface roughness, friction velocity, and inlet boundary wind speed are set as boundary layer parameters and boundary conditions.

4. The method as described in claim 3, characterized in that, The wind speed value at the preset height includes the average wind speed at a height of 10 meters and the average wind speed at a height of 100 meters. The calculation of surface roughness and friction speed based on the wind speed value at the preset height includes: Substitute the wind speed value at the preset height into the following first formula to calculate the surface roughness: Among them, z 0-1 For surface roughness; U 10ave-1 The average wind speed at a height of 10 meters; U 100ave-1 The average wind speed at a height of 100 meters; Substituting the surface roughness and the wind speed value at the preset height into the following second formula, the friction speed is calculated: Where, μ *-1 k is the friction velocity. * U is the Kármán constant; 100ave-1 The average wind speed at a height of 100 meters; z 0-1 This refers to surface roughness.

5. The method as described in claim 3, characterized in that, The calculation of the inlet boundary wind speed based on the surface roughness, friction velocity, and average elevation of the core calculation area includes: Obtain the average elevation of each grid point on the ground within the core computing area; The average elevation of the ground within the core computing area is calculated based on the average elevation of each grid point on the ground within the core computing area. The inlet boundary wind speed is calculated based on surface roughness, friction velocity, and the average elevation of the ground within the core calculation area.

6. The method as described in claim 1, characterized in that, The calculation of the long-term wind speed sequence for any point within the target area based on the simulated wind speed value and the wind speed in the mesoscale meteorological data includes: The wind acceleration factor is calculated based on the simulated wind speed value at any point within the target area and the wind speed value at the corresponding preset height in the mesoscale meteorological data. The wind acceleration factor is used to correct the long-term wind speed sequence at a preset height in the mesoscale meteorological data to obtain the long-term wind speed sequence at any point in the target area.

7. The method as described in claim 1, characterized in that, The mesoscale meteorological data is divided into multiple sectors, each sector corresponding to a different wind direction range. The step of plotting the wind speed map of the target area based on the long-term wind speed series includes: Obtain the long-term wind speed sequence of all sectors corresponding to any point in the target area; Calculate the average wind speed of all sectors at any point within the target area based on the long-term wind speed sequence of all sectors corresponding to any point within the target area. A wind speed map of the target area is drawn based on the average wind speed of all points within the target area.

8. A wind speed map plotting device, characterized in that, include: The acquisition module is used to acquire mesoscale meteorological data of the target area from a database used for recording meteorological data, and to acquire a topographic map of the target area, wherein the target area includes a core computing area and an outer buffer zone, and the topographic map of the target area contains the height data of the target area; The setting module is used to set boundary layer parameters and boundary conditions for the topographic map of the target area based on the mesoscale meteorological data. The simulation module is used to perform CFD simulation on the target area according to the boundary layer parameters and boundary conditions to obtain the simulated wind speed value at any point in the target area space, wherein the simulated wind speed value is related to the height. The calculation module is used to calculate the long-term wind speed sequence of any point in the target area based on the simulated wind speed value and the wind speed in the mesoscale meteorological data. A plotting module is used to plot the wind speed map of the target area based on the long-term wind speed sequence.

9. A wind speed map plotting system, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to implement the wind speed map plotting method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, When the instructions in the storage medium are executed by the processor corresponding to the wind speed map drawing system, the wind speed map drawing system is able to implement the wind speed map drawing method as described in any one of claims 1-7.

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