Photovoltaic project site selection method, system and equipment based on elevation grid and medium

Abstract

The invention provides a photovoltaic project site selection method, system and equipment based on an elevation grid, and a medium. The method comprises the following steps: acquiring elevation grid data; acquiring first raster data based on the elevation raster data; performing terrain screening based on the first raster data to obtain second raster data; performing shadow screening based on the first raster data to obtain third raster data; and obtaining the site selection area of the photovoltaic project based on the first raster data, the second raster data and the third raster data. The method can improve the efficiency and reliability of photovoltaic early-stage site selection work, and has the characteristics of high result accuracy and small operand.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of photovoltaic technology, and relates to a photovoltaic project site selection method, system, device and medium based on an elevation grid. BACKGROUND

[0002] A digital elevation model (DEM) is a digital simulation of a terrain surface or a digital representation of a terrain surface form through limited terrain elevation, and is usually stored in the form of a regular grid as elevation grid data. As the most important spatial information data in a geographic information system database and the core data system for terrain analysis, DEM plays an increasingly important role in scientific research, production planning, national defense construction and other fields.

[0003] A new energy photovoltaic power generation project is highly dependent on terrain data, and especially in the early site selection stage, the result of terrain analysis will directly affect the judgment basis for the arrangement area. Therefore, how to efficiently perform photovoltaic project site selection based on an elevation grid is a technical problem to be solved by those skilled in the art. SUMMARY

[0004] The application provides a photovoltaic project site selection method, system, device and medium based on an elevation grid, which is used to solve the problem of efficient photovoltaic project site selection based on an elevation grid.

[0005] In a first aspect, the application provides a photovoltaic project site selection method based on an elevation grid, which comprises: obtaining elevation grid data; obtaining first grid data based on the elevation grid data; performing terrain screening based on the first grid data to obtain second grid data; performing shadow screening based on the first grid data to obtain third grid data; and obtaining a site selection area of a photovoltaic project based on the first grid data, the second grid data and the third grid data.

[0006] In an implementation form of the first aspect, obtaining the first grid data based on the elevation grid data comprises: projecting the elevation grid data to a selected coordinate system to obtain projected grid data based on an intended site selection area of the photovoltaic project; splicing and extracting the projected grid data to obtain spliced grid data; and obtaining the first grid data by interpolating the spliced grid data based on an expected capacity of the photovoltaic project and a terrain complexity of the area.

[0007] In an implementation form of the first aspect, the terrain filtering based on the first grid data to obtain second grid data comprises: analyzing a terrain parameter of the first grid data to obtain slope direction data and slope ratio data; obtaining a maximum north slope limit, a maximum east-west slope limit, a maximum south slope limit, and a slope ratio limit; and filtering the slope direction data and the slope ratio data based on the maximum north slope limit, the maximum east-west slope limit, the maximum south slope limit, and the slope ratio limit to obtain the second grid data.

[0008] In an implementation form of the first aspect, the obtaining of the slope direction data and the slope ratio data comprises: starting from a north direction, performing slope direction analysis on the first grid data in a clockwise direction to obtain the slope direction data; and obtaining the slope ratio data based on slope data of the first grid data.

[0009] In an implementation form of the first aspect, the filtering of the slope direction data and the slope ratio data based on the maximum north slope limit, the maximum east-west slope limit, and the maximum south slope limit comprises: when the slope direction is between -90° and +90°, the slope ratio of the north component is not greater than the maximum north slope limit; in any slope direction, the slope ratio of the east component or the slope ratio of the west component is not greater than the maximum east-west slope limit; when the slope direction is between 90° and 270°, the slope ratio of the south component is not greater than the maximum south slope limit; and in any slope direction, the slope ratio data is not greater than the slope ratio limit.

[0010] In an implementation form of the first aspect, the shadow filtering based on the first grid data to obtain third grid data comprises: obtaining a solar incident angle of a solstice specified time period of a location of the photovoltaic project based on a selected step length; and obtaining an unshaded area of the solstice specified time period based on the solar incident angle of the solstice specified time period to obtain the third grid data.

[0011] In an implementation form of the first aspect, the obtaining of the site selection area of the photovoltaic project based on the first grid data, the second grid data, and the third grid data comprises: filtering an intended site selection area of the photovoltaic project based on the second grid data and the third grid data to obtain the site selection area; and generating contour lines based on the first grid data and superimposing the contour lines on the site selection area to obtain a visualization result of the site selection area.

[0012] In a second aspect, the application provides a photovoltaic project site selection system based on elevation grid, the system comprising: a first acquisition module configured to acquire elevation grid data; a second acquisition module configured to acquire first grid data based on the elevation grid data; a terrain screening module configured to perform terrain screening based on the first grid data to acquire second grid data; a shadow screening module configured to perform shadow screening based on the first grid data to acquire third grid data; and a site selection module configured to acquire a site selection area of a photovoltaic project based on the first grid data, the second grid data and the third grid data.

[0013] In a third aspect, the application provides an electronic device, comprising: a processor and a memory; the memory is configured to store a computer program, and the processor is configured to execute the computer program stored in the memory to enable the electronic device to perform the method.

[0014] In a fourth aspect, the application provides a computer readable storage medium having a computer program stored thereon, the computer program being executed to implement the method.

[0015] As described above, the photovoltaic project site selection method, system, device and medium based on elevation grid have the following beneficial effects:

[0016] 1. The application reduces the labor cost and improves the efficiency of the photovoltaic preliminary site selection work by processing the elevation grid data and performing terrain screening and shadow screening.

[0017] 2. The application directly analyzes the elevation grid data to obtain the site selection area of the photovoltaic project, significantly reduces the complexity of the operation and the precision loss in the data conversion process, and thus has the advantages of small amount of calculation and high accuracy of calculation results, improving the efficiency and reliability of the photovoltaic preliminary site selection work.

[0018] 3. The application reduces the precision loss in the data conversion process by converting the LAS data into elevation grid data, improving the reliability of the photovoltaic preliminary site selection work.

[0019] 4. The application combines the slope ratio and the aspect to analyze the site selection area that meets the requirements of the aspect and the slope ratio at the same time, and the result is more accurate and reasonable, improving the reliability of the photovoltaic preliminary site selection work.

[0020] 5. The application performs terrain analysis and shadow analysis based on grid data, reduces the demand for graphic computing devices, and is more in line with the existing device technology level, thereby improving the reliability of the photovoltaic preliminary site selection work as a whole. BRIEF DESCRIPTION OF DRAWINGS

[0021] Figure 1The diagram shown is a flowchart illustrating the photovoltaic project site selection method based on elevation grids as described in the embodiments of this application.

[0022] Figure 2 The diagram shown is a schematic representation of the process for obtaining first grid data based on the elevation grid data according to an embodiment of this application.

[0023] Figure 3 The diagram shows a process for obtaining second grid data by terrain filtering based on the first grid data, as described in an embodiment of this application.

[0024] Figure 4 The diagram shown is a flowchart illustrating the photovoltaic project site selection method based on elevation grids as described in the embodiments of this application.

[0025] Figure 5 The diagram shown is a structural schematic of the photovoltaic project site selection system based on elevation grids as described in an embodiment of this application.

[0026] Figure 6 The diagram shown is a structural connection diagram of the electronic device described in an embodiment of this application. Detailed Implementation

[0027] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0028] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. Therefore, the illustrations only show the components related to this application and are not drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0029] The technical solutions in the embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0030] Figure 1 The diagram shown is a flowchart illustrating the photovoltaic project site selection method based on elevation grids described in an embodiment of this application. Figure 1 As shown, the photovoltaic project site selection method based on elevation grid provided in this application includes steps S1 to S5.

[0031] S1. Obtain elevation raster data.

[0032] In some embodiments, the disclosed elevation raster data can be downloaded. Among them, the elevation raster data is a digital elevation model (DEM) that stores the terrain elevation information in a regular grid form, and each grid cell (pixel) records an elevation value, which can intuitively reflect the terrain relief characteristics. It can be widely used in terrain analysis, hydrological modeling, slope calculation, three-dimensional visualization and engineering planning fields, and has the characteristics of wide coverage and high processing efficiency.

[0033] In some embodiments, the elevation raster data can be obtained by converting the LAS point cloud data of the topographic survey result. Among them, the LAS (Lidar Data Exchange Format) point cloud data is a three-dimensional spatial data set obtained by laser radar scanning, which records the geometric information of the surface of the ground object in the form of discrete points, and each point contains three-dimensional coordinates (X, Y, Z) and attributes such as intensity and echo times. Through denoising and classification (separating ground points and non-ground points) processing of the LAS point cloud data, and then through interpolation algorithm (such as inverse distance weighting, Kriging or triangular mesh to raster) to convert the discrete ground points into regular grid elevation raster data.

[0034] S2, obtaining first raster data based on the elevation raster data.

[0035] After obtaining the elevation raster data, the elevation raster data needs to be preprocessed to obtain the first raster data. Figure 2 The flowchart of the photovoltaic project site selection method based on the elevation raster described in the embodiments of the present application is shown. As shown in Figure 2 Obtaining first raster data based on the elevation raster data includes steps S21 to S23.

[0036] S21, projecting the elevation raster data to a selected coordinate system to obtain projected raster data based on the intended site selection area of the photovoltaic project.

[0037] Specifically, according to the intended site selection area of the photovoltaic project, the degree band of the CGCS2000 coordinate system in which the center point of the intended site selection area is located is determined, and the elevation raster data is projected to the corresponding degree band of the CGCS2000 coordinate system. In some embodiments, the degree band of the CGCS2000 coordinate system mainly includes 3° sub-bands and 6° sub-bands, and through the coordinate conversion of the projection, the projection change can be reduced. Taking the 3° sub-band as an example, based on the longitude coordinate of the center point of the intended site selection area, the longitude coordinate is divided by 3° and rounded, that is, the degree band of the CGCS2000 coordinate system in which the center point is located is obtained, so that the elevation raster data can be projected to the corresponding degree band of the CGCS2000 coordinate system.

[0038] S22, splicing and extracting the projected raster data to obtain spliced raster data.

[0039] Specifically, after the projection conversion is completed, if there are multiple framed grid data, i.e., multiple projection grid data, the multiple projection grid data can be spliced into a complete grid. In addition, in order to keep the best longitude of the spliced data, the data can also be compressed, optimized, etc.

[0040] Then, the spliced grid data is extracted from the spliced data according to the intended site selection area. In order to ensure the reliability of the subsequent shadow analysis result, the spliced grid data is extracted based on the intended site selection area being enlarged to a suitable range to the south, so as to ensure that the shadow blocking factor is fully considered.

[0041] S23, based on the expected capacity of the photovoltaic project and the terrain complexity of the region, obtaining the lowest resolution to interpolate the spliced grid data to obtain the first grid data.

[0042] When the spliced grid data is interpolated, the selection of the resolution will directly affect the accuracy of the interpolation result - lower resolution may ignore local terrain undulations, and too high resolution will increase the calculation cost. Therefore, the expected capacity of the photovoltaic project and the terrain complexity of the region are used to obtain the lowest resolution to interpolate the spliced grid data.

[0043] In the planning of the photovoltaic project, the lowest grid resolution is determined based on the expected capacity (such as 10 MW or 100 MW) to ensure that the accuracy of the terrain analysis meets the requirements. For example, if the photovoltaic project covers a large area (such as square kilometers), a 30-meter resolution (such as SRTM data) can be used to balance the calculation efficiency and accuracy; if it is a distributed photovoltaic or needs to be finely selected (such as slope, shadow analysis), a higher resolution (such as 5-10 meter LiDAR data) is required.

[0044] Further, in the planning of the photovoltaic project, based on the terrain complexity of the region where the project is located, the resolution requirement is further refined based on the lowest grid resolution to ensure the adaptability of different terrains, thereby obtaining the final lowest resolution. For example, if the photovoltaic project is located in a plain or gently rolling hilly terrain, the terrain complexity is considered as level one, at this time the resolution can not be improved, and the lowest grid resolution determined based on the expected capacity is the lowest resolution obtained in step S23; if the photovoltaic project is located in a mountainous or steep hilly area, the terrain complexity is considered as level two, at this time the resolution level needs to be improved, such as a square kilometer level photovoltaic project located in a complex mountainous area, which requires DEM data with a resolution of 15 meters to 10 meters.

[0045] The mapping relationship between the terrain complexity and the specific terrain can be set by those skilled in the art.

[0046] It should be further noted that the minimum resolution can be determined by the person skilled in the art in combination with the project scale, terrain complexity and computing resources, and the application does not limit the way of obtaining the minimum resolution.

[0047] S3, performing terrain screening based on the first grid data to obtain second grid data.

[0048] In some embodiments, the terrain parameters of the first grid data are analyzed, and the second grid data is obtained by screening according to customizable standards. Figure 3 The flowchart of the photovoltaic project site selection method based on the elevation grid according to the embodiments of the application is shown in FIG. 1. Figure 3 As shown in FIG. 1, the terrain screening based on the first grid data to obtain the second grid data includes steps S31 to S33.

[0049] S31, analyzing the terrain parameters of the first grid data to obtain slope direction data and slope ratio data.

[0050] In some embodiments, the slope direction data is obtained by performing slope direction analysis on the first grid data in a clockwise direction with the north direction as the starting point. The slope direction refers to the azimuth angle of the terrain slope surface, with the north direction as the reference 0°, and the angle increases in a clockwise direction (e.g., 90° for east, 180° for south, and 270° for west), and the value range is 0°-360°, which is used to completely represent the horizontal direction of the slope surface.

[0051] In some embodiments, the slope ratio data is obtained based on the slope data of the first grid data. Assuming that the slope ratio is i and the slope is r, then:

[0052] i=tan(r)*100%

[0053] Wherein, the slope value r can be calculated based on the elevation change rate of the pixel neighborhood by using the GIS spatial analysis tool (such as the Slope tool of ArcGIS, the slope algorithm of QGIS or the gdaldem slope command of GDAL), and the output result is expressed in degrees (0°-90°) or percentage slope.

[0054] S32, obtaining the maximum north slope limit, the maximum east-west slope limit, the maximum south slope limit and the slope ratio limit.

[0055] S33, screening the slope direction data and the slope ratio data based on the maximum north slope limit, the maximum east-west slope limit, the maximum south slope limit and the slope ratio limit to obtain the second grid data.

[0056] In some embodiments, the maximum north slope limit, the maximum east-west slope limit, and the maximum south slope limit can be custom limits. In some embodiments, the maximum east-west slope limit actually includes a maximum east slope limit and a maximum west slope limit, both of which are the same threshold value. Then, filtering the slope direction data and the slope ratio data based on the maximum north slope limit, the maximum east-west slope limit, the maximum south slope limit, and the slope ratio limit includes:

[0057] When the slope direction is between -90° and +90°, the slope ratio of the positive north component is not greater than the maximum north slope limit.

[0058] For any slope direction, the slope ratio of the positive east component or the slope ratio of the positive west component is not greater than the maximum east-west slope limit.

[0059] When the slope direction is between 90° and 270°, the slope ratio of the positive south component is not greater than the maximum south slope limit.

[0060] For any slope direction, the slope ratio data is not greater than the slope ratio limit.

[0061] In some embodiments, the slope ratio limit is an overall limit, and the slope ratio data is not greater than the slope ratio limit for any slope direction means that no matter which direction the slope surface faces (i.e., all possible slope directions θ ∈ [0°, 360°]), the slope ratio of the region cannot exceed the set threshold value.

[0062] In some embodiments, the maximum north slope limit condition is C1, the maximum east-west slope limit condition is C2, the maximum south slope limit condition is C3, and the slope ratio limit condition is C4. Then, we have:

[0063] |i*sin(θ)|≤C2;

[0064] -C3≤i*cos(θ)≤C1;

[0065] i≤C4

[0066] That is, the second grid data is actually obtained by overall analyzing the slope ratio and the slope direction based on the custom standard, so as to obtain a terrain arrangement region that satisfies the custom standard at each slope direction and slope ratio.

[0067] In other embodiments, in addition to overall filtering based on the slope direction and the slope ratio, the slope angle can also be directly used for filtering analysis to obtain a terrain arrangement region that satisfies the custom standard.

[0068] S4, performing shadow filtering based on the first grid data to obtain third grid data.

[0069] In some embodiments, the shadow screening based on the first grid data to obtain third grid data comprises: obtaining the solar incident angle of the solstice specified time period of the location of the photovoltaic project based on a selected step; obtaining the unobstructed area of the solstice specified time period based on the solar incident angle of the solstice specified time period to obtain the third grid data.

[0070] For example, the solar incident angle of the solstice true solar time 09:00-15:00 of the location of the photovoltaic project is calculated at a step of 1 hour, and the area of the terrain shadow obstruction is calculated accordingly, and then the results of each hour are integrated to obtain the unobstructed area of the solstice true solar time 09:00-15:00. That is, the third grid data actually includes the shadow arrangement area.

[0071] S5, obtaining the site selection area of the photovoltaic project based on the first grid data, the second grid data and the third grid data.

[0072] In some embodiments, obtaining the site selection area of the photovoltaic project based on the first grid data, the second grid data and the third grid data comprises: screening the intended site selection area of the photovoltaic project based on the second grid data and the third grid data to obtain the site selection area; generating contour lines based on the first grid data and superimposing them on the site selection area to obtain the visualization result of the site selection area.

[0073] That is, the terrain arrangement area in the second grid data and the shadow arrangement area in the third grid data are integrated to screen the intended site selection area of the photovoltaic project to obtain the site selection area, and the contour lines are generated by the first grid data to obtain the contour lines, which are collectively presented in a visual manner.

[0074] Figure 4 A flowchart of the photovoltaic project site selection method based on the elevation grid according to the embodiments of the present application is shown. As shown in Figure 4 the first step is to download the publicly available elevation grid data and convert the LAS point cloud data to the elevation grid data to obtain the elevation grid data to be analyzed. Then, the elevation grid data to be analyzed is projected, spliced and spliced to obtain the spliced grid data, and then the interpolation processing is performed. The processed data is analyzed for slope and slope direction to screen based on the custom standard, i.e. overall analysis, to obtain the terrain arrangement area. At the same time, the solar incident angle of the current true solar time 09:00-15:00 is calculated based on the processed data, and the terrain shadow obstruction area is calculated accordingly. Finally, the site selection area is integrated and calculated based on the terrain arrangement area and the terrain shadow obstruction area, and the visualization result is obtained.

[0075] Therefore, the application can improve the efficiency and reliability of the photovoltaic early-stage site selection work, and has the characteristics of high result accuracy and small calculation amount.

[0076] The protection scope of the elevation grid-based photovoltaic project site selection method described in the embodiments of the application is not limited to the execution order of the steps listed in the embodiments, and any scheme achieved by increasing, reducing or replacing the steps of the prior art according to the principles of the application is included in the protection scope of the application.

[0077] Please refer to Figure 5 , which shows the structure principle diagram of the elevation grid-based photovoltaic project site selection system described in the embodiments of the application. As Figure 5 indicated, the application provides an elevation grid-based photovoltaic project site selection system, which comprises a first acquisition module 91, a second acquisition module 92, a terrain screening module 93, a shadow screening module 94 and a site selection module 95.

[0078] The first acquisition module 91 is configured to acquire elevation grid data.

[0079] The second acquisition module 92 is configured to acquire first grid data based on the elevation grid data.

[0080] The terrain screening module 93 is configured to perform terrain screening based on the first grid data to acquire second grid data.

[0081] The shadow screening module 94 is configured to perform shadow screening based on the first grid data to acquire third grid data.

[0082] The site selection module 95 is configured to acquire a site selection area of a photovoltaic project based on the first grid data, the second grid data and the third grid data.

[0083] It should be noted that the principles of the first acquisition module 91, the second acquisition module 92, the terrain screening module 93, the shadow screening module 94 and the site selection module 95 correspond to the method steps in the above embodiments one by one, and therefore will not be described here.

[0084] The elevation grid-based photovoltaic project site selection system described in the embodiments of the application can implement the elevation grid-based photovoltaic project site selection method described in the application, but the implementation device of the elevation grid-based photovoltaic project site selection method described in the application includes but is not limited to the structure of the elevation grid-based photovoltaic project site selection system listed in the embodiments, and any structure deformation and replacement of the prior art according to the principles of the application is included in the protection scope of the application.

[0085] In several embodiments provided in the present application, it should be understood that the disclosed system or method can be implemented in other manners. For example, the division of the system embodiments described above is merely an example, and the division of the modules / units can be different, for example, some modules / units can be combined or integrated into another module / unit, or some features can be ignored or not executed. In addition, the display or discussion of the coupling or direct coupling or communication connection between the modules / units can be indirect coupling or communication connection through some interfaces, devices or modules / units, and can be electrical, mechanical or other forms.

[0086] The modules / units described as separated components can or can not be physically separated, and the components displayed as modules / units can or can not be physical modules, i.e., can be located in one place or distributed on multiple network units. Some or all of the modules / units can be selected according to actual needs to achieve the purpose of the embodiments of the present application. For example, the functional modules / units in each embodiment of the present application can be integrated into a processing module, or each module / unit can be physically present separately, or two or more modules / units can be integrated into one module / unit.

[0087] Those of ordinary skill in the art should further appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of the examples have been described in general terms in the above description. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0088] Please refer to Figure 6 , which shows a structural connection diagram of an electronic device according to the embodiments of the present application. As Figure 6 indicated, the present embodiment provides an electronic device 1, which comprises a processor 11 and a memory 12; the memory 12 is used to store a computer program, and the processor 11 is used to execute the computer program stored in the memory, so that the electronic device 1 executes the method.

[0089] The processor 11 mentioned above can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0090] The aforementioned memory 12 may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device.

[0091] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed, implements the method for accurately locating faulty lines in a power distribution network.

[0092] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing a processor. The program can be stored in a computer-readable storage medium, which is a non-transitory medium, such as random access memory, read-only memory, flash memory, hard disk, solid-state drive, magnetic tape, floppy disk, optical disk, and any combination thereof. The storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. This available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., digital video disc (DVD)), or a semiconductor medium (e.g., solid-state drive (SSD)).

[0093] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0094] The above embodiments are only illustrative of the principles of the present application and its effects, and are not intended to limit the present application. Any modification or change made by any person skilled in the art without departing from the spirit and scope of the present application shall be covered by the claims of the present application.

Claims

1. A method for photovoltaic project siting based on elevation raster, characterized in that, The method comprises: obtaining elevation raster data; obtaining first raster data based on the elevation raster data; performing terrain screening based on the first raster data to obtain second raster data; performing shadow screening based on the first raster data to obtain third raster data; obtaining a site selection area of a photovoltaic project based on the first raster data, the second raster data and the third raster data.

2. The elevation raster-based photovoltaic project siting method of claim 1, wherein, Obtaining first raster data based on the elevation raster data comprises: projecting the elevation raster data to a selected coordinate system to obtain projected raster data based on an intended site selection area of the photovoltaic project; stitching and extracting the projected raster data to obtain stitched raster data; interpolating the stitched raster data at a minimum resolution to obtain the first raster data based on an expected capacity of the photovoltaic project and a terrain complexity of a region where the photovoltaic project is located.

3. The elevation raster-based photovoltaic project siting method of claim 1, wherein, Performing terrain screening based on the first raster data to obtain second raster data comprises: analyzing terrain parameters of the first raster data to obtain aspect data and slope ratio data; obtaining a maximum north slope limit, a maximum east-west slope limit, a maximum south slope limit and a slope ratio limit; screening the aspect data and the slope ratio data based on the maximum north slope limit, the maximum east-west slope limit, the maximum south slope limit and the slope ratio limit to obtain the second raster data.

4. The elevation raster-based photovoltaic project siting method of claim 1, wherein, Obtaining aspect data and slope ratio data comprises: performing aspect analysis on the first raster data in a clockwise direction with a due north direction as a starting point to obtain the aspect data; obtaining the slope ratio data based on slope data of the first raster data.

5. The elevation raster-based photovoltaic project siting method of claim 3, wherein, Screening the aspect data and the slope ratio data based on the maximum north slope limit, the maximum east-west slope limit and the maximum south slope limit comprises: when the aspect is between -90° and +90°, the slope ratio of the due north component is not greater than the maximum north slope limit; in any aspect, the slope ratio of the due east component or the slope ratio of the due west component is not greater than the maximum east-west slope limit; when the aspect is between 90° and 270°, the slope ratio of the due south component is not greater than the maximum south slope limit; and in any aspect, the slope ratio data is not greater than the slope ratio limit.

6. The elevation raster-based photovoltaic project siting method of claim 1, wherein, Performing shadow screening based on the first raster data to obtain third raster data comprises: obtaining a solar incident angle of a solstice day specified time period of a location of the photovoltaic project based on a selected step length; obtaining an unobstructed area of the solstice day specified time period based on the solar incident angle of the solstice day specified time period to obtain the third raster data.

7. The elevation raster based photovoltaic project siting method of claim 1, wherein, Obtaining a site selection area of a photovoltaic project based on the first raster data, the second raster data and the third raster data comprises: screening an intended site selection area of the photovoltaic project based on the second raster data and the third raster data to obtain the site selection area; generating contour lines based on the first raster data and superimposing the contour lines on the site selection area to obtain a visualization result of the site selection area.

8. A high-elevation raster-based photovoltaic project siting system, characterized by, The system comprises: a first obtaining module configured to obtain elevation raster data; a second obtaining module configured to obtain first raster data based on the elevation raster data; a terrain screening module configured to perform terrain screening based on the first raster data to obtain second raster data; a shadow screening module configured to perform shadow screening based on the first raster data to obtain third raster data; a site selection module configured to obtain a site selection area of a photovoltaic project based on the first raster data, the second raster data and the third raster data.

9. An electronic device, comprising: The electronic device comprises a processor and a memory; The memory is configured to store a computer program, and the processor is configured to execute the computer program stored in the memory, so that the electronic device performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed, implements the method according to any one of claims 1 to 7.

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