Regional partitioning method and device, electronic equipment and readable storage medium

Abstract

The invention discloses a region partitioning method and device, electronic equipment and a readable storage medium, and relates to the technical field of region partitioning, the method comprises the following steps: obtaining topographic data of a to-be-partitioned region, the to-be-partitioned region comprising a plurality of triangular mesh units; dividing the plurality of triangular mesh units into a plurality of triangular mesh unit groups according to the topographic data of the to-be-partitioned region and a preset grouping threshold range; based on the topographic data of the triangular mesh units in each triangular mesh unit group, converting the plurality of triangular mesh unit groups into a plurality of first partitions; and performing feasibility analysis on the plurality of first partitions, and converting the plurality of first partitions into a plurality of second partitions according to a feasibility analysis result. The method and the device have the effects of improving the efficiency and the precision of partitioning and processing large-scale operation.

Description

Technical Field

[0001] This application relates to the field of regional zoning technology, and in particular to a regional zoning method, apparatus, electronic device and readable storage medium. Background Technology

[0002] As a crucial sector for renewable energy development, the photovoltaic (PV) industry is experiencing robust growth driven by the energy transition. In PV projects, the installation area needs to be pre-divided into zones to facilitate installation design by engineers. However, the current primary method of zone division is manual division by engineers based on topographic maps. This approach is not only inefficient but also lacks precision and has limited capacity for handling large-scale operations. Summary of the Invention

[0003] The purpose of this application is to at least solve one of the technical problems existing in the prior art, and to provide a regional partitioning method, apparatus, electronic device and readable storage medium, which aims to improve the efficiency and accuracy of partitioning and to be able to handle large-scale operations.

[0004] In a first aspect, embodiments of this application provide a method for regional partitioning, including: Obtain terrain data of the region to be partitioned, wherein the region to be partitioned includes multiple triangular grid cells; Based on the terrain data of the region to be partitioned and the preset grouping threshold range, the multiple triangular mesh units are divided into multiple triangular mesh unit groups; Based on the terrain data of the triangular mesh cells in each of the triangular mesh cell groups, the multiple triangular mesh cell groups are converted into multiple first partitions; A feasibility analysis is performed on multiple first partitions, and based on the results of the feasibility analysis, the multiple first partitions are converted into multiple second partitions.

[0005] According to the technical solution of the embodiments of this application, at least the following beneficial effects are achieved: Before partitioning the region to be partitioned, the triangular mesh cells in the region to be partitioned are first grouped. Since the region to be partitioned includes multiple triangular mesh cells, and each triangular mesh cell has corresponding attribute data, the data to be processed by grouping multiple triangular mesh cells is intuitive and clear, without the need for complex calculations. Therefore, grouping multiple triangular mesh cells first can effectively divide the region to be partitioned roughly, reduce the amount of data processing in subsequent partitioning, and thus improve partitioning efficiency, so as to enable the processing of large-scale operations. In addition, the triangular mesh cell itself is also a kind of partition. Therefore, the triangular mesh cell group can be converted into the first partition. After obtaining the first partition, a feasibility analysis of multiple first partitions is also required to improve the accuracy and precision of the final partitioning result.

[0006] According to some embodiments of this application, the preset grouping threshold range includes a slope threshold range and a slope aspect threshold range.

[0007] According to some embodiments of this application, the step of converting multiple triangular mesh cell groups into multiple first partitions based on terrain data of triangular mesh cells in each triangular mesh cell group includes: Based on the coordinate data of all triangular mesh cells in each of the triangular mesh cell groups, the multiple triangular mesh cell groups are converted into multiple first partitions.

[0008] According to some embodiments of this application, the step of converting multiple triangular mesh cell groups into multiple first partitions based on the coordinate data of all triangular mesh cells in each triangular mesh cell group includes: Based on the coordinate data of all triangular mesh cells in each of the triangular mesh cell groups, the outer envelope of each of the triangular mesh cell groups is obtained through a preset algorithm; Multiple first partitions are obtained based on the outer envelope of each of the triangular mesh unit groups.

[0009] According to some embodiments of this application, it also includes: The attribute data of each of the first partitions is analyzed, and the outer envelope of each of the triangular mesh unit groups, as well as the attribute data of each of the first partitions, are visualized on the image of the region to be partitioned.

[0010] According to some embodiments of this application, the feasibility analysis of the plurality of first partitions includes: The first partition with the largest area among the multiple first partitions is taken as the first priority partition, and the remaining first partitions are analyzed in order of decreasing area.

[0011] According to some embodiments of this application, the feasibility analysis of the remaining first partitions in descending order of area includes: Feasibility analysis is performed on the remaining first partitions and the first priority partitions in descending order of area.

[0012] Secondly, embodiments of this application provide an operation control device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the regional partitioning method described in the first aspect above.

[0013] Thirdly, embodiments of this application provide an electronic device including the operation control device described in the second aspect above.

[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the territorial partitioning method as described in the first aspect above.

[0015] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0016] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0017] The present application will be further described below with reference to the accompanying drawings and embodiments; Figure 1 This is a flowchart of a regional partitioning method provided in one embodiment of this application; Figure 2 This is a flowchart of a regional partitioning method provided in another embodiment of this application; Figure 3 This is a flowchart of a regional partitioning method provided in another embodiment of this application; Figure 4 This is a flowchart of a regional partitioning method provided in another embodiment of this application; Figure 5 This is a flowchart of a regional partitioning method provided in another embodiment of this application; Figure 6 This is a flowchart of a regional partitioning method provided in another embodiment of this application; Figure 7 This is a two-dimensional visualization diagram of the regional zoning results provided in another embodiment of this application; Figure 8 This is a three-dimensional visualization diagram of the regional zoning results provided in another embodiment of this application; Figure 9 This is a data visualization diagram of the regional zoning results provided in another embodiment of this application; Figure 10 This is a schematic diagram of an operation control device for executing a regional partitioning method according to an embodiment of this application. Detailed Implementation

[0018] This section will describe in detail the specific embodiments of this application. Preferred embodiments of this application are shown in the accompanying drawings. The purpose of the drawings is to supplement the textual description with graphics, so that people can intuitively and vividly understand each technical feature and the overall technical solution of this application, but they should not be construed as limiting the scope of protection of this application.

[0019] In the description of this application, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0020] In the description of this application, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0021] In the description of this application, unless otherwise expressly defined, terms such as "setup," "installation," and "connection" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this application in conjunction with the specific content of the technical solution.

[0022] The various embodiments of the regional zoning method of this application will be further described below with reference to the accompanying drawings.

[0023] like Figure 1 As shown, Figure 1 This is a flowchart of a regional partitioning method provided in one embodiment of this application. The regional partitioning method may include, but is not limited to, steps S110, S120, S130 and S140.

[0024] Step S110: Obtain terrain data of the region to be partitioned, which includes multiple triangular grid cells; Step S120: Based on the terrain data of the area to be partitioned and the preset grouping threshold range, divide multiple triangular grid cells into multiple triangular grid cell groups. Step S130: Based on the terrain data of the triangular mesh cells in each triangular mesh cell group, convert multiple triangular mesh cell groups into multiple first partitions; Step S140: Perform a feasibility analysis on multiple first partitions, and convert the multiple first partitions into multiple second partitions based on the feasibility analysis results.

[0025] Understandably, dividing the area to be partitioned into multiple zones is primarily for more efficient planning, design, and construction. Partitioning allows for better analysis of the terrain, sunlight conditions, and environmental factors in different areas, thereby optimizing the layout and installation of photovoltaic modules. After partitioning, engineers can conduct detailed analyses of the characteristics of each zone, such as adjusting the tilt angle or orientation of the modules to maximize power generation efficiency, while also more accurately assessing construction difficulty and costs. Furthermore, partitioning facilitates later operation and maintenance management, making it easier to locate and troubleshoot faults, and improving the overall system stability and power generation performance. It is understandable that the partitioning of the area to be partitioned can involve dividing the entire area into different zones without any selection, or it can involve some selection after partitioning based on specific needs.

[0026] In this embodiment, the topographic data of the area to be partitioned may include altitude, slope, aspect, surface undulation characteristics, surface cover type, soil properties, hydrological conditions, and potential obstacles. This data can help analyze the sunlight conditions, shading, and construction difficulty of different areas, thereby providing a basis for the site selection and component layout of photovoltaic power plants, ensuring maximum power generation efficiency and reducing construction costs. Furthermore, the topographic data of the area to be partitioned can also assist in assessing geological disaster risks and environmental impacts, providing reliable basic information for subsequent engineering design and construction.

[0027] It is understandable that the terrain data of the area to be partitioned is correlated with the triangular mesh cells of that area, because the triangular mesh cells are the basic structure of terrain modeling, and terrain data is mapped onto each node or cell of the triangular mesh cells, facilitating the subsequent construction of digital elevation models or more refined terrain surface models. Furthermore, the level of detail in the triangular mesh cells can supplement the expressive accuracy of the terrain data. In areas with limited terrain data, denser triangular mesh cells can compensate for the lack of terrain data through the attribute data of the triangular mesh cells. For example, the attribute data of the triangular mesh cells can be converted into data of the same type and format as the terrain data. Similarly, the level of detail in the terrain data can supplement the expressive accuracy of the triangular mesh cells. In areas with sparse triangular mesh cells, a large amount of terrain data can compensate for the lack of triangular mesh cells. For example, triangular mesh cells can be automatically drawn from the terrain data to more accurately reflect subtle changes in the terrain, such as steep slopes, ridges, or valleys. These mesh cells can then be used to calculate solar radiation, shading, and optimal component tilt angles in different areas, ensuring that each partitioned area meets design requirements.

[0028] It is important to note that the terrain data of the region to be partitioned and the attribute data of the triangular mesh cells of the region to be partitioned can compensate for each other. Before dividing multiple triangular mesh cells into multiple triangular mesh cell groups, the terrain data of the region to be partitioned corresponds to the attribute data of all triangular mesh cells. That is, each triangular mesh cell has its own attribute data and corresponding terrain data to describe the triangular mesh cell. The attribute data of each triangular mesh cell and the terrain data used to describe the triangular mesh cell can be partially the same type of data or completely different types of data.

[0029] In this embodiment, during the zoning process of the photovoltaic project, since the terrain data of the area to be zoned corresponds to the attribute data of all triangular mesh units, multiple triangular mesh units can be divided into multiple triangular mesh unit groups based on the terrain data of the area to be zoned and the preset grouping threshold range. Specifically, multiple triangular mesh units can be directly grouped according to some or all types of terrain data and the corresponding preset grouping threshold range. For example, if all terrain data is used for grouping, all triangular mesh units with an altitude of 500-600 meters, a slope of 5-15 degrees, facing south, and with a grassland surface can be grouped into the same group. This allows for comprehensive consideration of multiple factors, ensuring that the lighting conditions and construction feasibility of the area are optimal. If only some terrain data is grouped, for example, only the slope is considered, all mesh units with a slope less than 10 degrees can be grouped into one group, while mesh units with a slope greater than 25 degrees can be grouped into another group, and so on.

[0030] In one embodiment, multiple triangular grid units can be grouped according to a specific grouping threshold range to design refined classification standards for different engineering needs. For example, in the planning of desert photovoltaic power stations, "dust mobility index 3-5, surface roughness 0.1-0.3, annual average wind speed 6-8m / s" can be set as grouping conditions. Triangular grid units that meet these characteristics are classified as dune active areas. Special foundation reinforcement and wind and sand protection designs are required for these areas. In coastal tidal flat photovoltaic projects, "tidal inundation frequency 30%-50%, silt bearing capacity 80-100kPa, salt spray corrosion level C2" can be used as grouping thresholds. More corrosion-resistant support materials and waterproof electrical equipment are required for these areas. Thus, the grouping method based on a specific combination of multi-parameter thresholds can accurately identify areas with special engineering requirements, providing a basis for subsequent differentiated design.

[0031] Understandably, it's advisable to first analyze the terrain data of the triangular mesh cells, as the terrain data of the region to be partitioned and the terrain data of the triangular mesh cells may differ. The original terrain data of the region to be partitioned is continuous and complete global geographic information, containing all detailed geomorphic features of the region before discretization. In contrast, the terrain data of the triangular mesh cells, after grouping, is an expression of the continuous terrain after discretization. The terrain features within each triangular mesh cell group may be homogenized, using single parameters such as elevation and slope to represent the terrain attributes of the entire cell. For example, a hillside with complex actual slope variations that will not affect actual photovoltaic projects may be simplified into several triangular mesh cell groups with fixed slope values. Although this processing may lose subtle changes in local terrain, these changes are negligible in the partitioning process. Therefore, this processing can significantly improve computational efficiency.

[0032] Understandably, the terrain data based on triangular mesh cells is converted into multiple first partitions, mainly to improve the feasibility of engineering implementation while retaining key terrain features. This is because the original terrain data of the area to be partitioned, although accurate, is too complex. The terrain data of triangular mesh cells, through discretization and homogenization, reflects the overall trend of the terrain in the area to be partitioned, while filtering out unnecessary detail interference. This avoids the computational burden caused by overly accurate terrain data, while oversimplification will affect power generation efficiency.

[0033] In this embodiment, the conversion of multiple triangular mesh unit groups into multiple first partitions includes parametric clustering based on terrain features, that is, partitioning according to the numerical characteristics of the mesh units such as slope, aspect, and elevation, and merging adjacent triangular mesh units within the same triangular mesh unit group with similar terrain attributes into the same partition; it also includes spatial continuity conversion, that is, by identifying connected and similar triangular mesh units within the same triangular mesh unit group, forming continuous partitions with clear boundaries to avoid fragmented small areas; and it also includes engineering adaptability conversion, that is, further modifying the clustering and adjusting the partition boundaries according to actual construction conditions, for example, avoiding geological faults or preserving equipment transportation channels.

[0034] In one embodiment, multiple triangular mesh cell groups can be converted into multiple first partitions based on the terrain data of the triangular mesh cells and the differences between the terrain data of the area to be partitioned and the terrain data of the triangular mesh cells. This is because the two types of data are complementary. During the conversion process, the terrain data of the triangular mesh cells is mainly used because the terrain data of the triangular mesh cells has standardized and quantified characteristics, which facilitates automatic computer processing and large-scale analysis, and can quickly achieve the classification and aggregation of terrain features. The differences between the terrain data of the area to be partitioned and the terrain data of the triangular mesh cells are used as auxiliary reference data to maintain the terrain authenticity of the partitioning results and prevent the partition boundaries from becoming disconnected from the actual situation due to the oversimplification of the triangular mesh cells.

[0035] It is understandable that the number of first partitions is not necessarily the same as the number of triangular mesh cell groups. A triangular mesh cell group can have multiple first partitions, or multiple triangular mesh cell groups can be the first partitions.

[0036] In this embodiment, the feasibility analysis of multiple first zones may include not only the feasibility analysis of photovoltaic characteristics such as illumination conditions, power generation efficiency, and module layout, but also the feasibility analysis of geological stability, soil bearing capacity, and hydrological characteristics of the first zones to ensure the safety of the support foundation and electrical equipment; it may also include the feasibility analysis of infrastructure factors such as transportation conditions, construction difficulty, and grid connection distance; and it may also include the feasibility analysis of economic aspects such as calculating land costs, construction investment, and subsequent maintenance costs for different zones.

[0037] Understandably, when conducting feasibility analyses on multiple first zones, all available data can be used, including the original topographic data of the area to be zoned, the topographic data of the triangular grid cells, the differences between the topographic data of the area to be zoned and the topographic data of the triangular grid cells, etc.

[0038] For example, a geographic information system (GIS) can be used to integrate the original topographic data of the area to be partitioned, the topographic data of triangular grid units, the differences between the topographic data of the area to be partitioned and the topographic data of triangular grid units, as well as spatial information such as possible geological exploration reports, ecological protection red lines, and power grid layout maps. This allows for the construction of a three-dimensional site model. Engineering algorithms are then used to automatically calculate key technical parameters for each partition, such as solar radiation, earthwork volume, and cable laying distance. Historical meteorological data is also incorporated to predict the impact of extreme weather, and soil testing reports are combined to assess the difficulty of foundation treatment. Economic analysis can simulate the input-output ratio of different partitioning schemes using a cost database, while also considering local factors such as land rent and demolition compensation. Finally, an environmental expert assessment system can be introduced to score the ecological sensitivity of each partition. In this way, the feasibility analysis results are linked to the first partition to obtain the second partition. The output results can be visualized for each first partition, allowing staff to clearly and intuitively understand the characteristics of each partition.

[0039] In one embodiment, the feasibility analysis may further include output feasibility, that is, whether the analysis results can be effectively transformed into executable engineering solutions and decision-making basis. For example, output feasibility can first analyze whether the integrity of the output can be guaranteed, ensuring that the analysis report can clearly present the advantages, disadvantages and risk warnings of each partition, including various forms of expression such as visual maps and quantitative data tables; secondly, it can be an adaptability analysis for decision support, that is, whether the depth and focus of the output content can be automatically adjusted according to different usage scenarios.

[0040] Understandably, the second partition, obtained through secondary optimization, possesses more refined engineering applicability and higher development value compared to the first partition. The second partition is an optimized result formed by overlaying multi-dimensional feasibility analyses, including construction feasibility, economic return, and environmental compatibility, based on the initial coarse screening of the first partition. Its boundary delineation relies not only on terrain features but also comprehensively considers actual construction conditions and operational needs. Unlike the first partition, which primarily reflects natural terrain features, the second partition may disrupt the original combination of some grid units. For example, it may divide areas on the same slope into mechanical construction zones and manual construction zones based on construction difficulty, or adjust the partition shape according to grid connection conditions to shorten cable distances.

[0041] In another embodiment of the geographical zoning method provided in this application, the preset grouping threshold range includes a slope threshold range and a slope aspect threshold range. Understandably, the preset grouping threshold ranges include slope threshold ranges and aspect threshold ranges. Setting the slope threshold range automatically filters suitable terrain areas for photovoltaic panel installation; for example, areas with a slope of 5-15 degrees are designated as optimal installation zones, avoiding increased support costs due to excessively steep slopes or drainage problems caused by excessively shallow slopes. Setting the aspect threshold range precisely identifies sunny sides; for example, south-facing slopes with an azimuth angle between 135-225 degrees are prioritized as high-power-generating-potential areas. Thus, by using slope and aspect threshold ranges, the objectivity of terrain data is preserved while incorporating industry experience, ensuring that the zoning results conform to both natural laws and engineering requirements, significantly improving planning efficiency.

[0042] like Figure 2 As shown, Figure 2 This is a flowchart of a regional partitioning method provided in another embodiment of this application; regarding the above step S130, it may include, but is not limited to, step S230.

[0043] Step S230: Based on the coordinate data of all triangular mesh cells in each triangular mesh cell group, convert multiple triangular mesh cell groups into multiple first partitions.

[0044] In this embodiment, all triangular mesh units in each triangular mesh unit group have corresponding coordinate data. This coordinate data can be the coordinate data of the triangular vertices of each triangular mesh unit. In other words, multiple triangular mesh unit groups can be converted into multiple first partitions based on the coordinate data of the triangular vertices of all triangular mesh units in each triangular mesh unit group.

[0045] For example, based on the coordinate data of all triangular vertices, adjacent triangular mesh cells with similar terrain features can be identified, that is, cells with elevation changes within a specific range and continuous spatial location can be converted into a first partition. In specific implementation, the normal vector of each triangular cell can be calculated first to determine its slope and aspect. Then, the adjacency relationship between triangular mesh cells can be determined based on the spatial distribution of vertex coordinates. Finally, combined with preset slope and aspect thresholds, adjacent triangular mesh cells that meet the conditions can be converted into the first partition.

[0046] Understandably, converting multiple triangular mesh unit groups into multiple first partitions based on the coordinate data of the triangular mesh units can avoid information loss and preserve the subtle features of the terrain. This is because when processing these coordinate data, the true surface area of ​​each triangular unit can be accurately calculated, rather than the projected area. In addition, three-dimensional coordinate data can provide a unified spatial reference for subsequent engineering applications, ensuring the consistency of spatial position and reducing errors whether it is overlaid with geological survey data or interfacing with engineering design drawings.

[0047] like Figure 3 As shown, Figure 3 This is a flowchart of a regional partitioning method provided in another embodiment of this application; regarding the above step S230, it may include, but is not limited to, steps S330 and S430.

[0048] Step S330: Based on the coordinate data of all triangular mesh cells in each triangular mesh cell group, obtain the outer envelope of each triangular mesh cell group through a preset algorithm; Step S430: Based on the outer envelope of each triangular mesh unit group, obtain multiple first partitions.

[0049] In this embodiment, based on the coordinate data of all triangular mesh units in each triangular mesh unit group, multiple triangular mesh unit groups are converted into multiple first partitions. The conversion can be a visual conversion, that is, the region of the triangular mesh unit group is displayed as the first partition in a visual way.

[0050] In this embodiment, the outer envelope is generated based on the coordinate data of the triangular mesh unit group. The outer envelope of each triangular mesh unit group can be obtained by a preset algorithm. The preset algorithm can be a convex hull algorithm or a boundary extraction algorithm. The convex hull algorithm can be Graham's scan algorithm or Andrew's monotonic chain algorithm. The convex hull algorithm can find the smallest convex polygon that contains all given coordinate points, thereby generating the outer envelope. The boundary extraction algorithm can identify the outer contour of arbitrary shapes, including possible concave parts. The boundary extraction algorithm is to traverse the edges of all triangular mesh units, identify the edges used by only one triangle as boundary edges, and then connect these boundary edges in an orderly manner to form a complete outer envelope.

[0051] Understandably, in the process of generating the outer envelope based on the coordinate data of the triangular mesh unit group, it is also necessary to handle various special cases through a preset algorithm, such as handling the hole areas that may exist in the mesh data, or distinguishing between the outer envelope and the inner boundary line.

[0052] Based on this, by generating an outer envelope from coordinate data of triangular mesh units, the transformation from discrete points to continuous boundaries is achieved. This allows the analysis results based on triangular mesh units to be presented in a more intuitive regional form. Furthermore, the generated outer envelope can be directly used to calculate the area of ​​a zone, draw planning maps, or overlay analysis with other planning maps. In actual photovoltaic projects, outer envelope data is often used for spatial relationship analysis with other engineering elements, such as checking safe distances from infrastructure like roads and pipelines, or assessing the visual impact on the surrounding environment. It is worth noting that the implementation of the preset algorithm needs to balance computational accuracy and efficiency. For large-scale photovoltaic fields, parallel computing or block processing strategies may be required, while for key areas with complex terrain, the density of boundary sampling can be appropriately increased.

[0053] like Figure 4 As shown, Figure 4 This is a flowchart of a regional partitioning method provided in another embodiment of this application; the regional partitioning method described above may also include, but is not limited to, step S530.

[0054] Step S530: Analyze the attribute data of each first partition, and visualize the outer envelope of each triangular grid cell group and the attribute data of each first partition on the image of the region to be partitioned.

[0055] Understandably, after obtaining multiple first zones, the attribute data of each first zone can be analyzed and visualized on the image of the area to be partitioned. This allows engineers to intuitively evaluate the rationality and optimization potential of the partitioning scheme. For example, the attribute data of the first zone includes data such as slope, aspect, and light intensity. By overlaying key parameters such as slope, aspect, and light intensity with different colors or textures on the satellite image or 3D terrain model of the area to be partitioned, engineers can clearly identify the spatial distribution patterns and potential problem areas of each first zone. For example, they can discover abnormal partition boundaries caused by abrupt changes in terrain, or contradictory areas where light conditions and slope conditions do not match.

[0056] like Figure 5 As shown, Figure 5 This is a flowchart of a regional partitioning method provided in another embodiment of this application; regarding the above step S140, it may also include, but is not limited to, step S240.

[0057] Step S240: Take the first partition with the largest area among the multiple first partitions as the first priority partition, and perform feasibility analysis on the remaining first partitions in descending order of area.

[0058] Understandably, larger zones typically represent more concentrated development areas, higher installed capacity, and lower unit costs. These characteristics constitute the most basic feasibility guarantee, resulting in higher feasibility scores for larger zones. In other words, larger zones are highly likely to become the core implementation areas of projects. From a practical perspective, the largest zones are often located in areas with relatively flat terrain and homogeneous conditions. These sites have fewer terrain constraints, a high degree of standardization in photovoltaic array layout, and relatively lower construction difficulty. Their development feasibility has already been preliminarily verified through early terrain data screening. Therefore, subsequent analysis can focus on smaller zones, as these scattered blocks are often distributed on the edge of the site or in areas with complex terrain, and may have various special restrictions or development risks. Their development value needs to be analyzed through more detailed feasibility analysis.

[0059] Based on this, in this embodiment, the feasibility analysis of multiple first partitions may include an analysis based on the rationality of spatial planning, which can then merge some unreasonable small partitions into larger areas. In other words, the first partition with the largest area among the multiple first partitions can be taken as the first priority partition. Feasibility analysis may not be performed on the first priority partition or only some simple feasibility analysis may be performed. For the remaining first partitions, feasibility analysis can be performed on the remaining first partitions in descending order of area.

[0060] like Figure 6 As shown, Figure 6 This is a flowchart of a regional partitioning method provided in another embodiment of this application; regarding the above step S240, it may also include, but is not limited to, step S340.

[0061] Step S340: Perform feasibility analysis by combining the remaining first partition and the first priority partition in descending order of area.

[0062] Understandably, when conducting feasibility analyses for the remaining first-zone areas (excluding the largest first-zone area) in descending order of area, one can either perform the feasibility analysis based on the attribute data of each remaining first-zone individually, or combine each remaining first-zone with the first-priority zone for feasibility analysis. This is because the first-priority zone, as the largest core area, may have already set the development tone for the entire photovoltaic power station in terms of its location and layout, and the subsequent evaluation of zones needs to be coordinated with it to form an overall plan. Therefore, when analyzing the smaller first-zone areas, it is necessary to combine each remaining first-zone with the first-priority zone individually, for example, by checking key factors such as whether the terrain transition between the two is natural.

[0063] In one embodiment, feasibility analysis is performed on the remaining first partitions and first priority partitions in descending order of area. This analysis can involve assessing the spatial planning rationality of the remaining first partitions and first priority partitions. For example, it can analyze whether there are any overlapping portions between the remaining first partitions and first priority partitions. If overlapping portions exist, they are subtracted from the remaining first partitions. In this way, each remaining first partition and first priority partition is analyzed separately. In another embodiment, when performing the combined analysis on each remaining first partition and first priority partition, when dealing with the smallest area first partition, it is not necessary to combine the smallest area first partition with the first priority partition for analysis. Instead, the spatial planning rationality of the smallest area first partition can be analyzed separately. For example, if the area of ​​the smallest area first partition is less than a preset fixed area value, it can be directly merged into the nearest first partition. If the area of ​​the smallest area first partition is not less than the preset fixed area value, it can then be combined with the first priority partition for analysis.

[0064] In one embodiment, reference Figure 7 , Figure 8 and Figure 9 , Figure 7 This is a two-dimensional visualization diagram of the regional zoning results provided in another embodiment of this application. Figure 8 This is a three-dimensional visualization diagram of the regional zoning results provided in another embodiment of this application. Figure 9 This is a data visualization diagram of the regional zoning results provided in another embodiment of this application.

[0065] Based on the regional partitioning methods described in the above embodiments, the following presents various embodiments of the operation control device, electronic device, and computer-readable storage medium of this application.

[0066] like Figure 10 As shown, Figure 10 This is a schematic diagram of an operation control device for executing a regional partitioning method according to an embodiment of this application. The operation control device 1000 implemented in this application includes: a processor 1020, a memory 1010, and a computer program stored in the memory 1010 and executable on the processor 1020, wherein... Figure 10 The example uses a processor 1020 and a memory 1010.

[0067] The processor 1020 and the memory 1010 can be connected via a bus or other means. Figure 10 Taking the example of a connection between China and Israel via a bus.

[0068] Memory 1010, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory 1010 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 1010 may optionally include remotely located memories 1010 relative to processor 1020, which can be connected to the operation control device 1000 via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0069] Those skilled in the art will understand that Figure 10 The device structure shown does not constitute a limitation on the operation control device 1000, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0070] exist Figure 10 In the operation control device 1000 shown, the processor 1020 can be used to call the control program stored in the memory 1010, thereby implementing the above-described regional partitioning method. Specifically, the non-transitory software program and instructions required to implement the regional partitioning method of the above embodiment are stored in the memory 1010, and when executed by the processor 1020, the regional partitioning method of the above embodiment is executed.

[0071] It is worth noting that, since the operation control device 1000 of this application embodiment can execute the regional partitioning method of any of the above embodiments, the specific implementation method and technical effect of the operation control device 1000 of this application embodiment can refer to the specific implementation method and technical effect of the regional partitioning method of any of the above embodiments.

[0072] Furthermore, one embodiment of this application also provides an electronic device that includes the operation control device described in the above embodiment.

[0073] It is worth noting that, since the electronic device of this application embodiment includes the operation control device of the above embodiments, and the operation control device of the above embodiments can execute the regional partitioning method of any of the above embodiments, the specific implementation method and technical effect of the electronic device of this application embodiment can refer to the specific implementation method and technical effect of the regional partitioning method of any of the above embodiments.

[0074] Furthermore, one embodiment of this application provides a computer-readable storage medium storing computer-executable instructions for performing the aforementioned regional partitioning method. Exemplarily, the above-described method is executed... Figures 1 to 6 The methods and steps in the text.

[0075] It is worth noting that, since the computer-readable storage medium of this application embodiment is capable of executing the regional partitioning method of any of the above embodiments, the specific implementation and technical effects of the computer-readable storage medium of this application embodiment can be referred to the specific implementation and technical effects of the regional partitioning method of any of the above embodiments.

[0076] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which may include computer storage media or non-transitory media and communication media or transient media. As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc DVD or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0077] In the several embodiments provided in this application, it should be understood that the disclosed systems, instruments, and methods can be implemented in other ways. For example, the instrument embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between instruments or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0078] It should also be understood that the various implementation methods provided in this application can be combined arbitrarily to achieve different technical effects.

[0079] The embodiments of this application have been described in detail above with reference to the accompanying drawings. However, this application is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of this application.

Claims

1. A method for regional zoning, characterized in that, include: Obtain terrain data of the region to be partitioned, wherein the region to be partitioned includes multiple triangular grid cells; Based on the terrain data of the region to be partitioned and the preset grouping threshold range, the multiple triangular mesh units are divided into multiple triangular mesh unit groups; Based on the terrain data of the triangular mesh cells in each of the triangular mesh cell groups, the multiple triangular mesh cell groups are converted into multiple first partitions; A feasibility analysis is performed on multiple first partitions, and based on the results of the feasibility analysis, the multiple first partitions are converted into multiple second partitions.

2. The regional zoning method according to claim 1, characterized in that, The preset grouping threshold range includes the slope threshold range and the aspect threshold range.

3. The regional zoning method according to claim 1, characterized in that, The process of converting multiple triangular mesh cell groups into multiple first partitions based on terrain data from triangular mesh cells in each of the triangular mesh cell groups includes: Based on the coordinate data of all triangular mesh cells in each of the triangular mesh cell groups, the multiple triangular mesh cell groups are converted into multiple first partitions.

4. The regional zoning method according to claim 3, characterized in that, The step of converting multiple triangular mesh cell groups into multiple first partitions based on the coordinate data of all triangular mesh cells in each triangular mesh cell group includes: Based on the coordinate data of all triangular mesh cells in each of the triangular mesh cell groups, the outer envelope of each of the triangular mesh cell groups is obtained through a preset algorithm; Multiple first partitions are obtained based on the outer envelope of each of the triangular mesh unit groups.

5. The regional zoning method according to claim 4, characterized in that, Also includes: The attribute data of each of the first partitions is analyzed, and the outer envelope of each of the triangular mesh unit groups, as well as the attribute data of each of the first partitions, are visualized on the image of the region to be partitioned.

6. The regional zoning method according to claim 1, characterized in that, The feasibility analysis of multiple first partitions includes: The first partition with the largest area among the multiple first partitions is taken as the first priority partition, and the remaining first partitions are analyzed in order of decreasing area.

7. The regional zoning method according to claim 6, characterized in that, The feasibility analysis of the remaining first partitions in descending order of area includes: Feasibility analysis is performed on the remaining first partitions and the first priority partitions in descending order of area.

8. An operation control device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the program to implement the territorial partitioning method as described in any one of claims 1 to 7.

9. An electronic device, characterized in that, Includes the operation control device as described in claim 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to perform the zoning method as described in any one of claims 1 to 7.

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