A method, device and storage medium for determining arrangement of photovoltaic modules

Abstract

The application discloses a kind of photovoltaic module arrangement determination method, device, equipment and storage medium.The method comprises: obtaining the contour discrete point of target area, based on the contour discrete point, the target area is divided into at least two first regional blocks, according to the distance between the contour discrete points in the first regional block, determine the initial triangular network, to complete the initial triangular network determination task, based on the boundary line of the first regional block and the initial triangular network, determine target triangular network, based on the target triangular network, establish the topographic model of the target area, and determine the arrangement of photovoltaic module according to the topographic model.The technical scheme of the embodiment of the application solves the problems of low modeling accuracy, unreasonable arrangement capacity of photovoltaic module and subsequent power generation loss of photovoltaic power station by twice triangular network division.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power plant technology, and in particular to a method, apparatus, equipment and storage medium for determining the arrangement of photovoltaic modules. Background Technology

[0002] With the vigorous implementation of "dual carbon" policies such as carbon peaking and carbon neutrality, and the rapid development of the new energy market, photovoltaic power generation is becoming increasingly important.

[0003] Typically, a photovoltaic (PV) power generation system consists of PV arrays, PV combiner equipment (including PV combiner boxes, DC distribution cabinets, and DC cables), inverters, AC power distribution equipment, step-up transformers, energy storage and control devices, wiring systems, and monitoring systems. Large-scale PV power plants are often located in mountainous areas with complex terrain. A Digital Elevation Model (DEM) is usually created based on the local topography to determine the arrangement of the PV modules.

[0004] However, this conventional modeling method suffers from low modeling accuracy, which leads to a loss of photovoltaic module layout capacity and subsequent photovoltaic power plant power generation. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and storage medium for determining the arrangement of photovoltaic modules, in order to solve the problem of unreasonable photovoltaic module arrangement caused by low modeling accuracy.

[0006] In a first aspect, embodiments of the present invention provide a method for determining the arrangement of photovoltaic modules, comprising:

[0007] Obtain discrete contour points of the target area, and divide the target area into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points;

[0008] In response to the initial triangulation determination task being triggered, an initial triangulation network is determined based on the distance between discrete points on the contour lines in the first region block to complete the initial triangulation network determination task, wherein the first region block contains the initial triangulation network;

[0009] Based on the boundary line of the first region block and the initial triangulation network, a target triangulation network is determined, wherein the target triangulation network includes the initial triangulation network;

[0010] Based on the target triangular network, a terrain model of the target area is established, and the arrangement of photovoltaic modules is determined according to the terrain model.

[0011] Secondly, embodiments of the present invention provide a device for determining the arrangement of photovoltaic modules, comprising:

[0012] The first region determination module is used to obtain the discrete contour points of the target region and divide the target region into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points.

[0013] An initial triangulation network determination module is configured to determine an initial triangulation network based on the distance between discrete points on the contour lines of the first region block in response to the initial triangulation network determination task being triggered, thereby completing the initial triangulation network determination task, wherein the first region block contains the initial triangulation network.

[0014] A target triangulation network determination module is used to determine a target triangulation network based on the boundary line of the first region block and the initial triangulation network, wherein the target triangulation network includes the initial triangulation network;

[0015] The module for determining the layout of photovoltaic modules is used to establish a terrain model of the target area based on the target triangular network, and to determine the layout of photovoltaic modules according to the terrain model.

[0016] Thirdly, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0017] At least one processor;

[0018] and memory that is communicatively connected to at least one processor;

[0019] The memory stores a computer program that can be executed by at least one processor, which enables the at least one processor to perform the method for determining the arrangement of photovoltaic modules described in the first aspect.

[0020] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions for causing a processor to execute the method for determining the arrangement of photovoltaic modules described in the first aspect.

[0021] The photovoltaic module layout determination scheme provided in this embodiment of the invention obtains the contour line discrete points of a target area, divides the target area into at least two first region blocks based on the contour line discrete points, wherein the first region block contains the contour line discrete points, responds to the initial triangulation network determination task being triggered, determines an initial triangulation network based on the distance between the contour line discrete points in the first region block to complete the initial triangulation network determination task, wherein the first region block contains the initial triangulation network, determines a target triangulation network based on the boundary line of the first region block and the initial triangulation network, wherein the target triangulation network contains the initial triangulation network, establishes a terrain model of the target area based on the target triangulation network, and determines the layout of photovoltaic modules based on the terrain model. By adopting the above technical solution, the target area is divided into multiple first region blocks based on the discrete points of contour lines. Then, based on the distance between the discrete points of contour lines in each first region block, an initial triangular network is formed in each first region block. Then, based on the boundary lines of each first region block and the initial triangular network therein, the target triangular network is determined. Finally, based on the target triangular network, the terrain model of the target area can be established, and the layout of photovoltaic modules can be determined. Through the division of the triangular network twice, the problems of low modeling accuracy, unreasonable photovoltaic module layout capacity, and subsequent photovoltaic power plant power generation loss that exist in direct terrain modeling of the target area are solved.

[0022] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a method for determining the arrangement of photovoltaic modules according to Embodiment 1 of the present invention;

[0025] Figure 2 This is a flowchart of a method for determining the arrangement of photovoltaic modules according to Embodiment 2 of the present invention;

[0026] Figure 3 This is a schematic diagram of the splicing of a target triangular network according to Embodiment 2 of the present invention;

[0027] Figure 4This is a schematic diagram of a photovoltaic module arrangement determination device according to Embodiment 3 of the present invention;

[0028] Figure 5 This is a schematic diagram of the structure of an electronic device provided according to Embodiment 4 of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. In the description of this invention, unless otherwise stated, "a plurality of" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.

[0031] Example 1

[0032] Figure 1 The flowchart of a method for determining the arrangement of photovoltaic modules is provided in Embodiment 1 of the present invention. This embodiment can be applied to the situation of determining the arrangement of photovoltaic modules. The method can be executed by a device for determining the arrangement of photovoltaic modules. The device for determining the arrangement of photovoltaic modules can be implemented in hardware and / or software. The device for determining the arrangement of photovoltaic modules can be configured in an electronic device. The electronic device can be composed of two or more physical entities or a single physical entity.

[0033] like Figure 1 As shown, the method for determining the arrangement of photovoltaic modules provided in Embodiment 1 of the present invention specifically includes the following steps:

[0034] S101. Obtain the discrete contour points of the target area, and divide the target area into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points.

[0035] In this embodiment, the area where photovoltaic modules are to be arranged can be taken as the target area. Then, the contour points of the target area are obtained. Based on the contour points and relevant parameters of the target area, such as the number of contour points and the area of ​​the target area, the target area can be divided into multiple region blocks, which are the first region blocks. The terrain of the target area can be a complex area such as mountains. The method of obtaining the contour points includes, but is not limited to, scattering the contour lines of the target area to obtain the contour points.

[0036] S102. In response to the initial triangulation network determination task being triggered, an initial triangulation network is determined based on the distance between discrete points of the contour lines in the first region block to complete the initial triangulation network determination task, wherein the first region block contains the initial triangulation network.

[0037] In this embodiment, after determining multiple first region blocks, an initial triangulation network determination task is triggered. In response to the triggering of this task, the task is executed for each first region block, dividing the triangle network according to the distance between discrete contour points to obtain the initial triangulation network. Specifically, the discrete contour points in each first region block can be connected to form the initial triangulation network, and the number of first region blocks is the same as the number of initial triangulation networks.

[0038] S103. Based on the boundary line of the first region block and the initial triangular network, determine the target triangular network, wherein the target triangular network includes the initial triangular network.

[0039] In this embodiment, the boundary lines of multiple first region blocks can be used as feature lines to stitch together the initial triangular networks contained within each of the multiple first region blocks, resulting in a complete triangular network, which is the target triangular network. Typically, a target region contains one target triangular network. The function of the feature lines is to provide feature point data for stitching together the multiple initial triangular networks, thereby completing the stitching of the initial triangular networks to obtain the target triangular network.

[0040] S104. Based on the target triangular network, establish a terrain model of the target area, and determine the arrangement of photovoltaic modules according to the terrain model.

[0041] In this embodiment, based on the target triangulation network within the target area, a terrain model of the target area can be established using a preset method, such as data interpolation. Based on the terrain model, information such as the shadow distribution of different slopes in the target area can be analyzed, thereby determining the arrangement of photovoltaic modules.

[0042] The method for determining the arrangement of photovoltaic modules provided in this embodiment of the invention involves obtaining discrete contour points of a target area, dividing the target area into at least two first region blocks based on the discrete contour points, wherein each first region block contains the discrete contour points, determining an initial triangulation network based on the distance between the discrete contour points in the first region blocks in response to the triggering of an initial triangulation network determination task, wherein each first region block contains the initial triangulation network, determining a target triangulation network based on the boundary lines of the first region blocks and the initial triangulation network, wherein the target triangulation network contains the initial triangulation network, establishing a terrain model of the target area based on the target triangulation network, and determining the arrangement of photovoltaic modules based on the terrain model. The technical solution of this invention divides the target area into multiple first region blocks based on discrete contour points. Then, based on the distance between discrete contour points in each first region block, an initial triangular network is formed in each first region block. Next, based on the boundary line of each first region block and the initial triangular network therein, a target triangular network is determined. Finally, based on the target triangular network, a terrain model of the target area can be established, and the arrangement of photovoltaic modules can be determined. Through the division of the triangular network twice, this solution solves the problems of low modeling accuracy, unreasonable photovoltaic module arrangement capacity, and subsequent photovoltaic power plant power generation loss that exist in directly modeling the terrain of the target area.

[0043] Example 2

[0044] Figure 2 This is a flowchart of a method for determining the arrangement of photovoltaic modules according to Embodiment 2 of the present invention. The technical solution of the present invention is further optimized based on the above optional technical solutions, and provides a specific method for determining the arrangement of photovoltaic modules.

[0045] Optionally, the step of obtaining discrete contour points of the target region and dividing the target region into at least one first region block based on the discrete contour points includes: obtaining contour lines of the target region; discretizing the contour lines to obtain discrete contour points; determining central region feature points from the discrete contour points based on a preset feature extraction algorithm; classifying the discrete contour points based on the central region feature points using a preset classification algorithm; and dividing the target region into at least two first region blocks according to the classification results. The advantage of this approach is that, based on the characteristics of the discrete contour points, the preset classification algorithm reasonably divides the target region into multiple first region blocks, providing support for improving modeling accuracy.

[0046] Optionally, determining the initial triangular network based on the distance between discrete contour points in the first region block includes: using a preset triangular mesh growth algorithm, determining multiple adjacent and non-overlapping initial triangles based on the initial discrete points, wherein the initial discrete points are the two contour point discrete points corresponding to the minimum distance between discrete contour points in the first region block; and determining the initial triangular network based on the multiple initial triangles. The advantage of this setup is that by using a preset triangular mesh growth algorithm to stitch together discrete contour points in different first region blocks to form an initial triangular network, the accuracy and speed of modeling are improved.

[0047] Optionally, determining the target triangular network based on the boundary line of the first region block and the initial triangular network includes: using a preset boundary feature extraction algorithm to extract boundary limit point features from the initial triangular network, and determining boundary limit points from the contour discrete points of the initial triangular network based on the boundary limit point features, wherein the boundary limit points include multiple contour discrete points; using the preset triangular network growth algorithm to determine multiple adjacent and non-overlapping target triangles based on the boundary line of the first region block and the initial limit points, wherein the initial limit points are the two boundary limit points corresponding to the minimum distance between boundary limit points in different first region blocks; and determining the target triangular network based on the multiple target triangles. The advantage of this setup is that by using the preset boundary feature extraction algorithm and the preset triangular network growth algorithm to stitch the initial triangular network into the target triangular network, the boundary of the target triangular network more closely reflects the actual geographical conditions of the target region.

[0048] like Figure 2 As shown in Embodiment 2 of the present invention, a method for determining the arrangement of photovoltaic modules specifically includes the following steps:

[0049] S201. Obtain the contour lines of the target area, and discretize the contour lines to obtain discrete points of the contour lines.

[0050] Specifically, you can first obtain the contour lines of the target area, and then use preset software, such as MATLAB, to discretize the contour lines of the target area to obtain discrete contour points.

[0051] S202. Based on a preset feature extraction algorithm, determine the feature points of the central region from the discrete points of the contour lines.

[0052] For example, if the preset feature extraction algorithm is the HOG (Histogram of Oriented Gradient) algorithm, then the HOG algorithm can be used to extract feature points with central region features from the discrete points of the contour lines, that is, central region feature points, as the dividing identifiers for the division of region blocks.

[0053] S203. Using a preset classification algorithm, classify the discrete points of the contour lines based on the feature points of the central region.

[0054] For example, if the preset classification algorithm is the SVM (Support Vector Machine) classification algorithm, then based on the determined feature points of the central region, the SVM classification algorithm can be used to classify the discrete contour points within the target region according to relevant parameters, thereby obtaining the classification result. These relevant parameters include the number of discrete contour points, the number of feature points in the central region, the size of the target region, and the region complexity, etc.

[0055] S204. Based on the classification results, the target region is divided into at least two first region blocks.

[0056] Specifically, based on the classification results obtained above, the target region is divided into multiple first region blocks. The region corresponding to each type of contour line discrete point in the classification results is one first region block.

[0057] Optionally, after obtaining the discrete contour points of the target area and dividing the target area into at least two first region blocks based on the discrete contour points, the method further includes:

[0058] The algorithm determines whether the density of the discrete contour points in the first region block meets a preset density requirement. If not, it performs spline interpolation on the discrete contour points in the first region block to make the density meet the preset density requirement. And / or, it determines whether the boundary line of the first region block is a closed curve. If not, it performs spline interpolation on the discrete contour points in the first region block to make the boundary line a closed curve. The advantage of this setup is that by checking the density of the discrete contour points and / or the closure of the boundary line of the first region block, the accuracy of the subsequent establishment of the target triangulation network and terrain model is ensured.

[0059] Specifically, the density of contour points in each first region block can be checked. If the density of contour points in the first region block is lower than a preset density threshold, spline interpolation can be performed on the contour points in the first region block to ensure that the density is no longer lower than the preset density threshold. Alternatively, the boundary line of the first region block can be checked. If the boundary line of the first region block is not a closed curve, spline interpolation can be performed on the contour points in the first region block to ensure that the boundary line is a closed curve. If the first region block undergoes the above checks and processing, the contour points and region block boundary lines involved in subsequent steps will all be the contour points and region block boundary lines after spline interpolation processing.

[0060] S205. In response to the initial triangulation network determination task being triggered, a preset triangulation network growth algorithm is used to determine multiple initial triangles that are adjacent to each other and do not overlap, based on the initial discrete points. The initial discrete points are the two contour line discrete points corresponding to the minimum distance between the contour line discrete points in the first region block.

[0061] For example, if the preset triangulation growth algorithm is the Delaunay triangulation generation algorithm, then the Delaunay triangulation generation algorithm can be used to find the two discrete points with the minimum distance between the discrete points of the contour lines in each first region block, that is, the initial discrete points. Connect these two discrete points with an edge as the baseline edge. Then, determine the nearest discrete point of the contour lines from the left or right side of the baseline edge and determine the third point. Connect the third point and the initial discrete point to obtain a triangle. Then, take the other two edges outside the baseline edge of the triangle as the new baseline edge, and execute the above steps of determining the third point and the triangle in sequence. Iterate through the remaining discrete points of the contour lines until all the discrete points of the contour lines have been processed, and then obtain multiple initial triangles that are adjacent to each other and do not overlap.

[0062] S206. Based on the plurality of initial triangles, determine an initial triangulation network to complete the task of determining the initial triangulation network.

[0063] Specifically, the multiple adjacent and non-overlapping initial triangles obtained above constitute the initial triangular network. Each first region block contains its own triangular network. The discrete contour points outside the central region feature points determined in step S202 can be used to correct the boundaries of the initial triangular network.

[0064] S207. Using a preset boundary feature extraction algorithm, extract boundary limit point features from the initial triangular network, and determine boundary limit points from the contour discrete points of the initial triangular network based on the boundary limit point features, wherein the boundary limit points include multiple contour discrete points.

[0065] For example, if the preset boundary feature extraction algorithm is the BorderDet boundary feature extraction algorithm, this algorithm can be used to extract boundary limit point features from the initial triangular network in each first region block, and the boundary limit points can be determined from the discrete points of the contour lines of the initial triangular network based on these features. In this embodiment, the boundary limit point can be understood as the limit point on the boundary line of the triangle in the initial triangular network, such as the discrete point corresponding to the outermost angle of the outermost triangle in the initial triangular network.

[0066] S208. Using the preset triangular mesh growth algorithm, based on the boundary line and initial limit point of the first region block, determine multiple target triangles that are adjacent to each other and do not overlap, wherein the initial limit point is the two boundary limit points corresponding to the minimum distance between the boundary limit points in different first region blocks.

[0067] Specifically, Figure 3 This is a schematic diagram of the splicing of a target triangular network, such as... Figure 3 As shown, the boundary line of the first region block can be used as the feature line. As described in the example above, the Delaunay triangulation generation algorithm can be used again to stitch together the boundary limit points of different first region blocks into multiple target triangles that are adjacent to each other and do not overlap.

[0068] S209. Determine the target triangulation network based on the multiple target triangles.

[0069] Specifically, the multiple adjacent and non-overlapping target triangles obtained above constitute the target triangulation network.

[0070] S210. Based on the target triangular network, establish a terrain model of the target area, and determine the arrangement of photovoltaic modules according to the terrain model.

[0071] Optionally, data interpolation can be performed on the target triangulation network to generate a Digital Elevation Model (DEM), which is a terrain model of the target area.

[0072] Optionally, determining the arrangement of photovoltaic modules based on the terrain model includes:

[0073] 1) Based on the terrain model, the slope and aspect of the target area are determined using a preset filtering and smoothing algorithm.

[0074] For example, if the preset filtering and smoothing algorithm is a third-order difference algorithm, the slope and aspect of the target area can be calculated based on the terrain model, thereby obtaining the calculation results of slope and aspect.

[0075] 2) Based on the slope and the slope direction, the target area is divided into at least two second area blocks.

[0076] Specifically, areas with similar slope and / or aspect can be grouped into one category according to a preset classification method. Based on the specific parameters of the slope and aspect of the target area, the target area can be divided into multiple second-level blocks. The number of categories and the number of second-level blocks can be the same.

[0077] 3) In response to the photovoltaic module layout task being triggered, the layout of the photovoltaic modules is determined according to the shadow distribution corresponding to the second area block to complete the photovoltaic module layout task.

[0078] Specifically, once the second area block is divided, a photovoltaic module placement task will be triggered. In response to the triggering of this photovoltaic module placement task, a true solar time shading distribution analysis operation will be performed on the slope within each second area block. Based on the analysis results, the specific placement method of the photovoltaic modules can be determined, thereby completing the photovoltaic module placement task.

[0079] Furthermore, the initial triangulation network determination task includes at least two parallel mesh determination subtasks, with different first region blocks corresponding to different mesh determination subtasks; the photovoltaic module layout task includes at least two parallel layout subtasks, with different second region blocks corresponding to different layout subtasks.

[0080] For example, if there are a different first region blocks, then there are also a subtasks for determining the grid in the initial triangulation network determination task; if there are b different second region blocks, then there are also b subtasks for arranging the photovoltaic modules in the arrangement task, where both a and b are greater than or equal to 2.

[0081] The photovoltaic module layout determination method provided in this invention utilizes a preset feature extraction algorithm to divide the target area into multiple first region blocks. Then, using a preset triangular mesh growth algorithm, an initial triangular network is formed in each first region block based on initial discrete points. Next, using a preset boundary feature extraction algorithm and a preset triangular mesh growth algorithm, a target triangular network is determined based on the boundary lines and initial limit points of the first region blocks. Finally, based on the target triangular network, a terrain model of the target area can be established, and the layout of photovoltaic modules can be determined. By utilizing the preset boundary feature extraction algorithm and the preset triangular mesh growth algorithm, the speed of terrain modeling is improved, the terrain modeling cycle is shortened, and the boundary of the triangular network is made to better fit the actual geographical conditions of the target area. As a result, the obtained terrain model is more consistent with the actual geographical conditions, avoiding the waste of the available layout area in the target area and improving the module layout capacity and power generation.

[0082] Based on the above embodiments, the method may further include:

[0083] The system determines the area of ​​the first region corresponding to each first region block. Based on the area of ​​the first region, it assigns a corresponding first processing core to the corresponding subtask of the grid, wherein the number of the first processing cores is positively correlated with the area of ​​the first region. Similarly, it determines the area of ​​the second region corresponding to each second region block. Based on the area of ​​the second region, it assigns a corresponding second processing core to the corresponding layout subtask, wherein the number of the second processing cores is positively correlated with the area of ​​the second region. The advantage of this setup is that, based on the positive correlation between region area and processing cores, processing cores are rationally allocated to the subtasks, allowing for parallel processing of the subtasks and saving time in determining the photovoltaic module layout.

[0084] For example, assuming the target region is denoted as A, as described above, the target region can be divided into n first region blocks, denoted as A0. 1 A 2 ,…,A n The area of ​​the first region is denoted as S. 1 ,S 2 ,…,S n If the processing time of the subtask corresponding to a unit area S is T, then the processing time of the subtask corresponding to the area of ​​the first region is T. i The definite expression is i = 1, 2, ..., n, T i This represents the processing time for the grid-determined subtask corresponding to the area of ​​the i-th first region. If the processor handling the grid-determined subtask has a total of M processing cores, then m cores can be allocated to each first region block. i There is a first processing core, and the expression for determining the first processing core is m. i =M*Ti / sum(T i ), m i This represents the number of first processing cores allocated to the grid-determined subtask corresponding to the i-th first region block, and sum() represents the summation operator, allowing the grid-determined subtasks corresponding to n first region blocks to be processed in parallel. If T i If the maximum value in (i = 1, 2, ..., n) is Tmax, then after Tmax, all grids are considered to have completed their subtasks. The number of first processing cores is positively correlated with the area of ​​the first region.

[0085] For example, as described above, if the target region A is divided into three equal second region blocks, denoted as A0... ′1 A ′2 A ′3 The area of ​​the second region is denoted as S′. 1 ,S′ 2 S′ 3 ,S ′i =S / 3, i=1,2,3, then m′ can be assigned to each second region block. i There is a second processing core, and the expression for determining the second processing core is m′. i =M / 3, m′ i This represents the number of second processing cores allocated to the arrangement subtask corresponding to the i-th second region block, enabling the arrangement subtasks corresponding to the three second region blocks to be processed in parallel. As described in the two examples above, the processing time of the parallelized arrangement subtask and the mesh determination subtask is Tmax + T. ′ max, compared to the serial processing time nTmax+3T ′ max, if n = 6, Tmax = T ′ If the maximum value is used, it can save nearly 1-2Tmax / 9Tmax = 7 / 9 of the serial processing time.

[0086] Example 3

[0087] Figure 4 This is a schematic diagram of a photovoltaic module arrangement determination device provided in Embodiment 3 of the present invention. Figure 4 As shown, the device includes: a first region determination module 301, an initial triangulation network determination module 302, a target triangulation network determination module 303, and a component layout determination module 304, wherein:

[0088] The first region determination module is used to obtain the discrete contour points of the target region and divide the target region into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points.

[0089] An initial triangulation network determination module is configured to determine an initial triangulation network based on the distance between discrete points on the contour lines of the first region block in response to the initial triangulation network determination task being triggered, thereby completing the initial triangulation network determination task, wherein the first region block contains the initial triangulation network.

[0090] A target triangulation network determination module is used to determine a target triangulation network based on the boundary line of the first region block and the initial triangulation network, wherein the target triangulation network includes the initial triangulation network;

[0091] The module for determining the layout of photovoltaic modules is used to establish a terrain model of the target area based on the target triangular network, and to determine the layout of photovoltaic modules according to the terrain model.

[0092] The photovoltaic module layout determination device provided in this embodiment of the invention divides the target area into multiple first region blocks based on contour line discrete points. Then, based on the distance between the contour line discrete points in each first region block, an initial triangular network is formed in each first region block. Next, based on the boundary line of each first region block and the initial triangular network therein, a target triangular network is determined. Finally, based on the target triangular network, a terrain model of the target area can be established, and the layout of the photovoltaic modules can be determined. By dividing the target area into two triangular networks, the device solves the problems of low modeling accuracy, unreasonable photovoltaic module layout capacity, and subsequent photovoltaic power plant power generation loss that exist when directly modeling the terrain of the target area.

[0093] Optionally, the device may also include:

[0094] The first processing module is used to determine whether the density of the discrete contour points in the first region block meets a preset density requirement after obtaining the discrete contour points of the target region and dividing the target region into at least two first region blocks based on the discrete contour points. If not, spline interpolation processing is performed on the discrete contour points in the first region block to make the density meet the preset density requirement.

[0095] The second processing module is used to determine whether the boundary line of the first region block is a closed curve. If not, spline interpolation is performed on the discrete points of the contour lines in the first region block to make the boundary line form a closed curve.

[0096] Optionally, the first region determination module 301 includes:

[0097] The discrete point determination unit is used to acquire the contour lines of the target area, discretize the contour lines, and obtain discrete points of the contour lines.

[0098] The feature point determination unit is used to determine the feature points of the central region from the discrete points of the contour lines based on a preset feature extraction algorithm.

[0099] A classification unit is used to classify the discrete points of the contour lines based on the feature points of the central region using a preset classification algorithm.

[0100] The first region block determination unit is used to divide the target region into at least two first region blocks according to the classification results.

[0101] Optionally, the initial triangulation network determination module 302 includes:

[0102] The initial triangle determination unit is used to determine multiple adjacent and non-overlapping initial triangles based on initial discrete points using a preset triangulation growth algorithm. The initial discrete points are the two contour line discrete points corresponding to the minimum distance between the contour line discrete points in the first region block.

[0103] An initial triangulation network determination unit is used to determine an initial triangulation network based on the plurality of initial triangles.

[0104] Optionally, the target triangulation network determination module 303 includes:

[0105] The boundary limit point determination unit is used to extract boundary limit point features from the initial triangular network using a preset boundary feature extraction algorithm, and determine the boundary limit points from the contour line discrete points of the initial triangular network based on the boundary limit point features, wherein the boundary limit points include multiple contour line discrete points.

[0106] The target triangle determination unit is used to determine multiple adjacent and non-overlapping target triangles based on the boundary lines and initial limit points of the first region block using the preset triangular mesh growth algorithm. The initial limit points are the two boundary limit points corresponding to the minimum distance between the boundary limit points in different first region blocks.

[0107] The target triangulation network determination unit is used to determine a target triangulation network based on the plurality of target triangles.

[0108] Optionally, the component layout determination module 304 includes:

[0109] The slope and aspect determination unit is used to determine the slope and aspect of the target area based on the terrain model and using a preset filtering and smoothing algorithm.

[0110] The second region block determination unit is used to divide the target area into at least two second region blocks according to the slope and the slope direction;

[0111] The module layout unit is used to determine the layout of the photovoltaic modules according to the shadow distribution corresponding to the second area block in response to the photovoltaic module layout task being triggered, so as to complete the photovoltaic module layout task.

[0112] Optionally, the initial triangulation network determination task includes at least two parallel mesh determination subtasks, with different first region blocks corresponding to different mesh determination subtasks; the photovoltaic module layout task includes at least two parallel layout subtasks, with different second region blocks corresponding to different layout subtasks.

[0113] Optionally, the device may also include:

[0114] The first processing core allocation module is used to determine the area of ​​the first region corresponding to each of the first region blocks, and to allocate the corresponding first processing core to the corresponding grid subtask based on the area of ​​the first region. The number of the first processing cores is positively correlated with the area of ​​the first region.

[0115] The second processing core allocation module is used to determine the area of ​​the second region corresponding to each second region block, and allocate corresponding second processing cores to the corresponding arrangement subtasks according to the area of ​​the second region, wherein the number of the second processing cores is positively correlated with the area of ​​the second region.

[0116] The photovoltaic module arrangement determination device provided in this embodiment of the invention can execute the photovoltaic module arrangement determination method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0117] Example 4

[0118] Figure 5 A schematic diagram of an electronic device 40 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0119] like Figure 5As shown, the electronic device 40 includes at least one processor 41 and a memory, such as a read-only memory (ROM) 42 or a random access memory (RAM) 43, communicatively connected to the at least one processor 41. The memory stores computer programs executable by the at least one processor. The processor 41 can perform various appropriate actions and processes based on the computer program stored in the ROM 42 or loaded into the RAM 43 from storage unit 48. The RAM 43 may also store various programs and data required for the operation of the electronic device 40. The processor 41, ROM 42, and RAM 43 are interconnected via a bus 44. An input / output (I / O) interface 45 is also connected to the bus 44.

[0120] Multiple components in electronic device 40 are connected to I / O interface 45, including: input unit 46, such as keyboard, mouse, etc.; output unit 47, such as various types of monitors, speakers, etc.; storage unit 48, such as disk, optical disk, etc.; and communication unit 49, such as network card, modem, wireless transceiver, etc. Communication unit 49 allows electronic device 40 to exchange information / data with other devices through computer grids such as the Internet and / or various telecommunications grids.

[0121] Processor 41 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 41 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 41 performs the various methods and processes described above, such as the method for determining the arrangement of photovoltaic modules.

[0122] In some embodiments, the method for determining the photovoltaic module arrangement may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 48. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 40 via ROM 42 and / or communication unit 49. When the computer program is loaded into RAM 43 and executed by processor 41, one or more steps of the method for determining the photovoltaic module arrangement described above may be performed. Alternatively, in other embodiments, processor 41 may be configured to perform the method for determining the photovoltaic module arrangement by any other suitable means (e.g., by means of firmware).

[0123] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0124] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0125] The computer equipment provided above can be used to execute the photovoltaic module arrangement determination method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0126] Example 5

[0127] In the context of this invention, the computer-readable storage medium may be a tangible medium, and the computer-executable instructions, when executed by a computer processor, are used to perform a method for determining the arrangement of photovoltaic modules, the method comprising:

[0128] Obtain discrete contour points of the target area, and divide the target area into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points;

[0129] In response to the initial triangulation determination task being triggered, an initial triangulation network is determined based on the distance between discrete points on the contour lines in the first region block to complete the initial triangulation network determination task, wherein the first region block contains the initial triangulation network;

[0130] Based on the boundary line of the first region block and the initial triangulation network, a target triangulation network is determined, wherein the target triangulation network includes the initial triangulation network;

[0131] Based on the target triangular network, a terrain model of the target area is established, and the arrangement of photovoltaic modules is determined according to the terrain model.

[0132] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by, or in conjunction with, an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0133] The computer equipment provided above can be used to execute the photovoltaic module arrangement determination method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0134] It is worth noting that in the embodiments of the photovoltaic module arrangement determination device described above, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0135] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for determining the arrangement of photovoltaic modules, characterized in that, include: Obtain discrete contour points of the target area, and divide the target area into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points; In response to the initial triangulation determination task being triggered, an initial triangulation network is determined based on the distance between discrete points on the contour lines in the first region block to complete the initial triangulation network determination task, wherein the first region block contains the initial triangulation network; Based on the boundary line of the first region block and the initial triangulation network, a target triangulation network is determined, wherein the target triangulation network includes the initial triangulation network; Based on the target triangulation network, a terrain model of the target area is established, and the arrangement of photovoltaic modules is determined according to the terrain model; The process further includes, after obtaining the discrete contour points of the target area and dividing the target area into at least two first region blocks based on the discrete contour points: Determine whether the density of the discrete contour points in the first region block meets a preset density requirement. If not, perform spline interpolation on the discrete contour points in the first region block to make the density meet the preset density requirement; and / or, Determine whether the boundary line of the first region block is a closed curve. If not, perform spline interpolation on the discrete points of the contour lines in the first region block to make the boundary line a closed curve.

2. The method according to claim 1, characterized in that, The step of obtaining discrete contour points of the target region and dividing the target region into at least two first region blocks based on the discrete contour points includes: Obtain the contour lines of the target area, and discretize the contour lines to obtain discrete points of the contour lines; Based on a preset feature extraction algorithm, feature points in the central region are determined from the discrete points of the contour lines; Using a preset classification algorithm, the discrete points of the contour lines are classified based on the feature points of the central region; Based on the classification results, the target region is divided into at least two first region blocks.

3. The method according to claim 1, characterized in that, The step of determining the initial triangulation network based on the distances between discrete points on the contour lines of the first region block includes: Using a preset triangular mesh growth algorithm, based on initial discrete points, multiple initial triangles that are adjacent to each other and do not overlap are determined. The initial discrete points are the two discrete points on the contour lines that correspond to the minimum distance between the discrete points on the contour lines in the first region block. Based on the multiple initial triangles, an initial triangular network is determined.

4. The method according to claim 3, characterized in that, The step of determining the target triangulation network based on the boundary line of the first region block and the initial triangulation network includes: Using a preset boundary feature extraction algorithm, boundary limit point features are extracted from the initial triangular network, and boundary limit points are determined from the contour line discrete points of the initial triangular network based on the boundary limit point features, wherein the boundary limit points include multiple contour line discrete points; Using the preset triangulation growth algorithm, based on the boundary line and initial limit point of the first region block, a number of mutually adjacent and non-overlapping target triangles are determined, wherein the initial limit point is the two boundary limit points corresponding to the minimum distance between the boundary limit points in different first region blocks. Based on the multiple target triangles, a target triangulation network is determined.

5. The method according to claim 1, characterized in that, Determining the arrangement of photovoltaic modules based on the terrain model includes: Based on the terrain model, the slope and aspect of the target area are determined using a preset filtering and smoothing algorithm; Based on the slope and the slope direction, the target area is divided into at least two second area blocks; In response to the photovoltaic module layout task being triggered, the layout of the photovoltaic modules is determined according to the shadow distribution corresponding to the second area block, so as to complete the photovoltaic module layout task.

6. The method according to claim 5, characterized in that, The initial triangulation network determination task includes at least two parallel mesh determination subtasks, with different mesh determination subtasks corresponding to different first region blocks; The photovoltaic module layout task includes at least two layout sub-tasks processed in parallel, with different layout sub-tasks corresponding to different second region blocks; The method further includes: Determine the area of ​​the first region corresponding to each first region block, and allocate corresponding first processing cores to the corresponding grid subtasks based on the area of ​​the first region, wherein the number of the first processing cores is positively correlated with the area of ​​the first region; Determine the area of ​​the second region corresponding to each second region block, and allocate corresponding second processing cores to the corresponding arrangement subtasks based on the area of ​​the second region, wherein the number of the second processing cores is positively correlated with the area of ​​the second region.

7. A device for determining the arrangement of photovoltaic modules, characterized in that, include: The first region determination module is used to obtain the discrete contour points of the target region and divide the target region into at least two first region blocks based on the discrete contour points, wherein the first region block contains the discrete contour points. An initial triangulation network determination module is configured to determine an initial triangulation network based on the distance between discrete points on the contour lines of the first region block in response to the initial triangulation network determination task being triggered, thereby completing the initial triangulation network determination task, wherein the first region block contains the initial triangulation network. A target triangulation network determination module is used to determine a target triangulation network based on the boundary line of the first region block and the initial triangulation network, wherein the target triangulation network includes the initial triangulation network; The component layout determination module is used to establish a terrain model of the target area based on the target triangular network, and determine the layout of the photovoltaic modules according to the terrain model; The device further includes: The first processing module is used to determine whether the density of the discrete contour points in the first region block meets a preset density requirement after obtaining the discrete contour points of the target region and dividing the target region into at least two first region blocks based on the discrete contour points. If not, spline interpolation processing is performed on the discrete contour points in the first region block to make the density meet the preset density requirement. The second processing module is used to determine whether the boundary line of the first region block is a closed curve. If not, spline interpolation is performed on the discrete points of the contour lines in the first region block to make the boundary line form a closed curve.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the method for determining the arrangement of photovoltaic modules according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for determining the arrangement of photovoltaic modules as described in any one of claims 1-6.

Images