Photovoltaic panel installation angle evaluation method and device, equipment and storage medium

Abstract

The invention discloses a photovoltaic panel installation angle evaluation method and device, equipment and a storage medium. The method comprises the following steps: determining first point cloud data of a target photovoltaic panel, and determining contour boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is formed by splicing a plurality of photovoltaic modules; dividing the target photovoltaic panel into a plurality of grid blocks based on the contour boundary information, and obtaining second point cloud data of each grid block; determining a first vector of the grid block based on the second point cloud data; the first vector is perpendicular to the grid block and points upwards; based on the first vector and the second vector, angle information of the grid blocks is determined, and based on the angle information of all the grid blocks, the installation angle of the target photovoltaic panel is evaluated; the second vector is a normal vector of the horizontal plane. According to the invention, whether the installation angles of all photovoltaic panels meet the design requirements is rapidly evaluated, and the angle determination efficiency and accuracy are improved.

Description

Technical Field

[0001] This invention relates to the field of new energy technology, and in particular to a method, apparatus, equipment and storage medium for evaluating the installation angle of photovoltaic panels. Background Technology

[0002] Photovoltaic power generation is an emerging renewable energy technology that has received widespread attention and promotion as an important component of new energy sources. In photovoltaic power generation systems, the installation angle of photovoltaic panels is a crucial factor in installation compliance verification, power generation efficiency assessment and optimization, operation and maintenance, and troubleshooting. Traditional methods for measuring the installation angle of photovoltaic panels mainly rely on manual measurement or the use of specialized equipment, which is time-consuming, labor-intensive, and inefficient. Furthermore, the determination process is significantly influenced by human factors, greatly affecting the accuracy of the determined photovoltaic panel installation angle. Summary of the Invention

[0003] This invention provides a method, apparatus, device, and storage medium for evaluating the installation angle of photovoltaic panels, so as to quickly evaluate whether the installation angle of all photovoltaic panels meets the design requirements and improve the efficiency and accuracy of angle determination.

[0004] According to one aspect of the present invention, a method for evaluating the installation angle of a photovoltaic panel is provided, the method comprising:

[0005] First point cloud data of the target photovoltaic panel is determined, and the outline boundary information of the target photovoltaic panel is determined based on the first point cloud data; the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together.

[0006] Based on the outline boundary information, the target photovoltaic panel is divided into multiple grid blocks, and the second point cloud data of each grid block is obtained;

[0007] Based on the second point cloud data, a first vector of the grid block is determined; the first vector is perpendicular to the grid block and points upward.

[0008] Based on the first vector and the second vector, the angle information of the grid block is determined, and based on the angle information of all the grid blocks, the installation angle of the target photovoltaic panel is evaluated; the second vector is the normal vector of the horizontal plane.

[0009] According to another aspect of the present invention, an evaluation device for the installation angle of a photovoltaic panel is provided, the device comprising:

[0010] An information determination module is used to determine the first point cloud data of the target photovoltaic panel and determine the outline boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together.

[0011] The point cloud data acquisition module is used to divide the target photovoltaic panel into multiple grid blocks based on the contour boundary information, and acquire the second point cloud data of each grid block;

[0012] A vector determination module is used to determine a first vector of the grid block based on the second point cloud data; the first vector is perpendicular to the grid block and points upward;

[0013] The evaluation module is used to determine the angle information of the grid blocks based on the first vector and the second vector, and to evaluate the installation angle of the target photovoltaic panel based on the angle information of all the grid blocks; the second vector is the normal vector of the horizontal plane.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the photovoltaic panel installation angle evaluation method according to any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the method for evaluating the installation angle of a photovoltaic panel as described in any embodiment of the present invention.

[0019] The technical solution of this invention involves determining the first point cloud data of a target photovoltaic panel, and then determining the contour boundary information of the target photovoltaic panel based on the first point cloud data. This allows the target photovoltaic panel to be divided into multiple grid blocks based on the contour boundary information, facilitating accurate estimation of the installation angle of the photovoltaic panel. Further, the second point cloud data of each grid block is acquired, and a first vector of the grid block is determined based on the second point cloud data. The angle information of the grid block is then determined based on the first and second vectors, enabling the evaluation of the installation angle of the target photovoltaic panel based on the angle information of all grid blocks. This allows for the identification of local deformation or uneven installation of the panel, enabling rapid evaluation of whether the installation angle of all photovoltaic panels meets design requirements, and improving the efficiency and accuracy of angle determination.

[0020] 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

[0021] 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.

[0022] Figure 1 This is a flowchart of a method for evaluating the installation angle of a photovoltaic panel according to an embodiment of the present invention;

[0023] Figure 2 This is an example diagram of a target photovoltaic panel with multiple grid blocks applicable according to embodiments of the present invention;

[0024] Figure 3 This is a schematic diagram of the first and second vectors applicable according to embodiments of the present invention;

[0025] Figure 4 This is a flowchart of another method for evaluating the installation angle of a photovoltaic panel according to an embodiment of the present invention;

[0026] Figure 5 This is a schematic diagram of the first and second directions applicable according to embodiments of the present invention;

[0027] Figure 6 This is a schematic diagram of the angle distribution of the target photovoltaic panel applicable to the embodiments of the present invention;

[0028] Figure 7 This is a schematic diagram of the structure of a photovoltaic panel installation angle evaluation device according to an embodiment of the present invention;

[0029] Figure 8 This is a schematic diagram of the structure of an electronic device that implements the method for evaluating the installation angle of a photovoltaic panel according to an embodiment of the present invention. Detailed Implementation

[0030] 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.

[0031] 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 the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises 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 apparatus.

[0032] Example 1

[0033] Figure 1 This is a flowchart illustrating a method for evaluating the installation angle of a photovoltaic panel, provided by an embodiment of the present invention. This embodiment is applicable to situations where the installation angle of a photovoltaic panel needs to be evaluated. This method can be executed by a photovoltaic panel installation angle evaluation device, which can be implemented in hardware and / or software. This photovoltaic panel installation angle evaluation device can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the method for evaluating the installation angle of a photovoltaic panel according to the present invention may include:

[0034] S110. Determine the first point cloud data of the target photovoltaic panel, and determine the outline boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together.

[0035] The first point cloud data is three-dimensional point cloud data. The contour boundary information can be used to describe the contour boundary of the target photovoltaic panel, and may include, but is not limited to, length, width, and position information.

[0036] Specifically, determining the contour boundary information of the target photovoltaic panel based on the first point cloud data can include: performing data preprocessing on the first point cloud data to obtain preprocessed first point cloud data; the data preprocessing operations can include denoising filtering and downsampling; denoising filtering can be done by using statistical filtering (removing outliers) or radius filtering (retaining dense panel points) to eliminate measurement noise; downsampling can be done by using voxel grid downsampling to reduce the number of point clouds, reducing the amount of subsequent computation, while preserving the overall shape of the panel. Furthermore, a preset contour extraction method is used to determine the contour boundary information of the target photovoltaic panel from the preprocessed first point cloud data.

[0037] When the preset contour extraction method is based on planar projection and 2D contour extraction, the specific process of determining the contour boundary information of the target photovoltaic panel can be as follows: project the preprocessed first point cloud data onto the fitting plane (or a 2D plane perpendicular to the normal vector) to convert it into two-dimensional point cloud data, then use the convex hull algorithm or contour detection method to obtain contour detail information, and then back-project the contour detail information back into three-dimensional space to obtain the contour boundary of the target photovoltaic panel.

[0038] When the preset contour extraction method is a geometric shape fitting method, the specific process of determining the contour boundary information of the target photovoltaic panel can be as follows: fit the preprocessed first point cloud data into the minimum bounding rectangle, and determine the contour boundary information of the target photovoltaic panel based on the minimum bounding rectangle.

[0039] Furthermore, after determining the contour boundary information of the target photovoltaic panel, the contour boundary information can be optimized to obtain updated contour boundary information. Optimization can involve using statistical methods to remove discrete noise points in the contour to avoid contour distortion; and / or using B-spline curves or moving averages to smooth the contour edges to eliminate jagged edges caused by point cloud discretization.

[0040] In an embodiment of the present invention, optionally, determining the first point cloud data of the target photovoltaic panel may include steps A1-A3:

[0041] Step A1: Obtain the third-point cloud data of the photovoltaic power station; the photovoltaic power station has multiple target photovoltaic panels.

[0042] Specifically, three-dimensional point cloud data, or third-party point cloud data, of photovoltaic power plants can be acquired using drones. The drone flies above the photovoltaic power plant and uses its onboard imaging equipment to photograph the plant, thus quickly obtaining point cloud data of the photovoltaic panels. The data format of third-party point cloud data is typically LAS format or other point cloud formats.

[0043] Step A2: Preprocess the third point cloud data to obtain the fourth point cloud data; the preprocessing includes at least one of the following operations: outlier deletion and data filtering on the first coordinate axis; the first coordinate axis is perpendicular to the ground.

[0044] Specifically, the process of deleting isolated points can be as follows: Based on the point cloud density, set the neighborhood radius and minimum number of neighbors, traverse the third point cloud data, determine the number of points in the neighborhood of each point, if the number of points is greater than or equal to the minimum number of neighbors, then determine that point as a core point; if the number of points is less than the minimum number of neighbors, then determine that point as an edge point, and if it falls into the neighborhood of other core points, it will be assigned to the corresponding cluster, otherwise it will be judged as a noise point; until all the third point cloud data has been traversed, the points that have not been assigned to any cluster are classified as isolated points, and the isolated points are deleted from the third point cloud data.

[0045] The purpose of the data filtering operation on the first coordinate axis is to retain points within a specific height range in order to more accurately identify photovoltaic panels. The specific process can be as follows: analyze the numerical distribution of the third point cloud data on the first coordinate axis, determine the preset range through interactive methods or automatic algorithms, then retain the points whose values ​​on the first coordinate axis are within the preset range, perform gridding on the retained points, and retain only the points with the largest values ​​on the first coordinate axis in each grid to extract the top points of the panel.

[0046] Step A3: Perform point cloud segmentation on the fourth point cloud data based on the clustering algorithm to obtain point cloud regions corresponding to multiple target photovoltaic panels, and determine the point cloud data of the point cloud region corresponding to the target photovoltaic panel as the first point cloud data of the target photovoltaic panel.

[0047] The clustering algorithm can be either density-based spatial clustering (DBSCAN) or K-means clustering.

[0048] Specifically, after identifying the point cloud regions corresponding to multiple target photovoltaic panels laid out in the photovoltaic power station, a unique panel identification information can be assigned to each target photovoltaic panel. This information is used to distinguish each target photovoltaic panel during subsequent visualization and to ensure that the first point cloud data of each target photovoltaic panel can be accurately extracted from the fourth point cloud data based on the panel identification information.

[0049] This invention involves acquiring third point cloud data of a photovoltaic power station with multiple target photovoltaic panels. The third point cloud data is then preprocessed to obtain fourth point cloud data. Preprocessing includes outlier removal and data filtering along a first coordinate axis. The first coordinate axis is perpendicular to the ground, ensuring that the point cloud data contains only the point clouds of each target photovoltaic panel. Then, a clustering algorithm is used to segment the fourth point cloud data, obtaining point cloud regions corresponding to multiple target photovoltaic panels. The point cloud data corresponding to each target photovoltaic panel is then identified as the first point cloud data for that target photovoltaic panel. This allows for simultaneous processing of a large number of photovoltaic panels, enabling batch angle estimation and significantly improving work efficiency. This invention is applicable to various types of photovoltaic power stations, including ground-mounted power stations and rooftop distributed systems, and has low requirements for point cloud data quality, demonstrating strong adaptability.

[0050] S120. Based on the contour boundary information, the target photovoltaic panel is divided into multiple grid blocks, and the second point cloud data of each grid block is obtained.

[0051] Specifically, based on the contour boundary information, the length, width, and coordinates of the four corners of the target photovoltaic panel are determined; the side length information of the grid blocks, including length and width, is determined; based on the side length information, the length and width information of the target photovoltaic panel, the number of rows and columns is divided, thereby dividing the target photovoltaic panel into multiple grid blocks; then, based on the position information of each grid block, the point cloud data of each grid block is extracted from the first point cloud data as the second point cloud data. For example, as shown... Figure 2 The image shown is an example of a target photovoltaic panel divided into multiple grid blocks. Figure 2 The grid can be divided into grid blocks of equal size, or it can be divided into grid blocks of unequal size.

[0052] Optionally, obtaining the second point cloud data for each grid block may include: extracting reference point cloud data of the grid block from the first point cloud data based on the position information of each grid block, determining the center coordinates of the grid block based on the reference point cloud data, and extracting point cloud data within a preset search radius from the second point cloud data as the second point cloud data, with the center coordinates of the grid block as the center.

[0053] Optionally, obtaining the second point cloud data for each grid block may further include: using the center line obtained through the center coordinates of the grid block as a reference, extracting point cloud data at a preset distance on both sides of the center line from the reference point cloud data as the second point cloud data.

[0054] S130. Based on the second point cloud data, determine the first vector of the grid block; the first vector is perpendicular to the grid block and points upward.

[0055] Specifically, the second point cloud data is fitted with a plane based on the least squares method to obtain the plane equation of the grid block, and the normal vector obtained by solving the plane equation of the grid block is used as the first vector of the grid block.

[0056] Optionally, determining the first vector of the grid block based on the second point cloud data may include: constructing a second covariance matrix of the second point cloud data, determining multiple second eigenvalues ​​of the second covariance matrix and the second eigenvectors corresponding to the second eigenvalues; and determining the second eigenvector corresponding to the smallest second eigenvalue among the second eigenvalues ​​as the first vector of the grid block.

[0057] S140. Based on the first and second vectors, determine the angle information of the grid blocks, and based on the angle information of all grid blocks, evaluate the installation angle of the target photovoltaic panel; the second vector is the normal vector of the horizontal plane.

[0058] Specifically, such as Figure 3 As shown, the target angle between the first vector and the second vector is determined, and the remainder of the target angle is used as the angle information of the grid block. The installation angle of the target photovoltaic panel is evaluated based on the angle information of all grid blocks.

[0059] The technical solution of this invention involves determining the first point cloud data of a target photovoltaic panel, and then determining the contour boundary information of the target photovoltaic panel based on the first point cloud data. This allows the target photovoltaic panel to be divided into multiple grid blocks based on the contour boundary information, facilitating accurate estimation of the installation angle of the photovoltaic panel. Further, the second point cloud data of each grid block is acquired, and a first vector of the grid block is determined based on the second point cloud data. The angle information of the grid block is then determined based on the first and second vectors, enabling the evaluation of the installation angle of the target photovoltaic panel based on the angle information of all grid blocks. This allows for the identification of local deformation or uneven installation of the panel, enabling rapid evaluation of whether the installation angle of all photovoltaic panels meets design requirements, and improving the efficiency and accuracy of angle determination.

[0060] Example 2

[0061] Figure 4 This is a flowchart illustrating another method for evaluating the installation angle of a photovoltaic panel, provided by an embodiment of the present invention. The technical solution of this embodiment further optimizes the process of evaluating the installation angle of the photovoltaic panel based on the above embodiments. This embodiment can be combined with various optional solutions in one or more of the above embodiments. Figure 4 As shown, the method for evaluating the installation angle of a photovoltaic panel according to the present invention may include:

[0062] S210. Determine the first point cloud data of the target photovoltaic panel, and determine the outline boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together.

[0063] S220. Construct the first covariance matrix of the first point cloud data, and determine multiple first eigenvalues ​​of the first covariance matrix and the first eigenvectors corresponding to the first eigenvalues.

[0064] S230. The direction of the first eigenvector corresponding to the largest first eigenvalue among the first eigenvalues ​​is determined as the first direction, and the direction perpendicular to the first direction and parallel to the target photovoltaic panel is determined as the second direction.

[0065] S240. Based on the first direction, the second direction, and the contour boundary information, the target photovoltaic panel is divided into multiple grid blocks.

[0066] Specifically, such as Figure 5 As shown, a local coordinate system is constructed with the first and second directions. Based on the local coordinate system, the target photovoltaic panel is divided into multiple grid blocks according to the contour boundary information.

[0067] Optionally, the contour boundary information includes the length information and width information of the target photovoltaic panel; based on the first direction, the second direction, and the contour boundary information, dividing the target photovoltaic panel into multiple grid blocks may include: determining the size information of the grid blocks based on the length information and width information; based on the size information, dividing the target photovoltaic panel into multiple grid blocks along the first direction and the second direction.

[0068] S250. Obtain the second point cloud data of each grid block, and based on the second point cloud data, determine the first vector of the grid block; the first vector is perpendicular to the grid block and points upward.

[0069] S260. Determine the target angle between the first vector and the second vector, and determine the result of taking the remainder of the target angle as the angle information of the grid block. Based on the angle information of all grid blocks, evaluate the installation angle of the target photovoltaic panel; the second vector is the normal vector of the horizontal plane.

[0070] Specifically, evaluating the installation angle of the target photovoltaic panel based on the angle information of all grid blocks may include steps B1 - B3:

[0071] Step B1. Generate an angle distribution diagram of the target photovoltaic panel based on the angle information of all grid blocks.

[0072] Specifically, generate an angle distribution diagram of the target photovoltaic panel according to the position information and angle information of each grid block, as Figure 6 shown as the distribution of the angle information of all grid blocks in the target photovoltaic panel.

[0073] Step B2. Determine the target average value of the angle information of all grid blocks, and determine the target average value as the predicted installation angle of the target photovoltaic panel.

[0074] Step B3. Evaluate the installation angle of the target photovoltaic panel based on the angle distribution diagram and the predicted installation angle.

[0075] Specifically, if the installation angle of the photovoltaic panel is within the preset angle range, it is determined as a qualified photovoltaic panel; the predicted installation angle can roughly reflect whether the installation angle of the target photovoltaic panel meets the requirements as a whole. And the installation angle of each grid block should also fall within the preset angle range. Then, if the number of grid blocks with angle information not within the preset angle range is greater than the preset number, there is a problem with the installation of the target photovoltaic panel. From the angle distribution diagram, it is also possible to more intuitively locate which local positions of the target photovoltaic panel have problems, so that adjustments can be made faster, achieving not only the estimation of the overall angle but also the identification of local deformation and uneven installation of the panel, providing more comprehensive quality assessment information. <0**********72> <0**********73>Optionally, in an embodiment of the present invention, after determining that the installation angle of the target photovoltaic panel meets the requirements, the shadow information of the target photovoltaic panel can be further determined based on the outline boundary information and solar azimuth information of the target photovoltaic panel. The shadow information includes the projected area and shadow position information.

[0077] Specifically, the solar altitude angle and azimuth angle are calculated based on the geographical location and date and time of the target photovoltaic panel. The solar altitude angle and azimuth angle are used as solar azimuth information. The solar azimuth information is converted into a solar direction vector in three-dimensional space. The solar direction vector represents the direction of sunlight.

[0078] Then, based on the contour boundary information, the first coordinates of the four corner points of the target photovoltaic panel are determined. The first coordinates of each corner point are projected along the solar direction vector to calculate the shadow information of the shadow points of the light and the ground. The shadow information includes the projection distance and the coordinates of the shadow points.

[0079] Specifically, the projection calculation of the first coordinate of each corner point along the solar direction vector to determine the shadow information of the shadow point of the ray and the ground may include: calculating the shadow information of each shadow point using a ray tracing algorithm; determining the projection distance of the shadow point by dividing the difference between the height of the corner point and the height of the ground by the z-component of the solar direction vector; and calculating the coordinates of the shadow point by adding the first coordinate of the corner point to the projection distance multiplied by the solar direction vector.

[0080] Furthermore, the shadow points corresponding to the four corner points are connected to form a shadow polygon. The projected area of ​​the target photovoltaic panel is determined based on the shadow polygon, and the position information of the shadow points is the shadow position information.

[0081] In addition, the shadow polygon can be divided into a mesh to generate a shadow mesh, which can then be added to the 3D scene for display. The display attributes and color of the shadow can be set to achieve the correct spatial relationship between the shadow and the panel and the ground.

[0082] In this embodiment of the invention, after determining that the installation angle of the target photovoltaic panel meets the requirements, the shadow information of the target photovoltaic panel can be further determined based on the outline boundary information and solar azimuth information of the target photovoltaic panel. This can effectively and accurately determine the projection of each target photovoltaic panel, which can be used in the fields of photovoltaic power plant planning and design, existing photovoltaic power plant renovation and optimization, photovoltaic power plant operation and maintenance management, and photovoltaic power generation prediction systems.

[0083] The technical solution of this invention involves determining first point cloud data of a target photovoltaic panel, and then determining the contour boundary information of the target photovoltaic panel based on the first point cloud data. The target photovoltaic panel is composed of multiple photovoltaic modules. A first covariance matrix of the first point cloud data is constructed, and multiple first eigenvalues ​​and corresponding first eigenvectors of the first covariance matrix are determined. The direction of the first eigenvector corresponding to the largest first eigenvalue is determined as a first direction, and the direction perpendicular to the first direction and parallel to the target photovoltaic panel is determined as a second direction, thus achieving accurate determination of the first and second directions. Based on the first direction, the second direction, and the contour boundary information, the target photovoltaic panel can be more accurately divided into multiple grid blocks. Second point cloud data of each grid block is obtained, and a first vector of the grid block is determined based on the second point cloud data. The target angle between the first and second vectors is determined, and the remainder of the target angle is determined as the angle information of the grid block. This facilitates the evaluation of the installation angle of the target photovoltaic panel based on the angle information of all grid blocks, enabling the identification of local deformation or uneven installation of the panel, and enabling rapid evaluation of whether the installation angle of all photovoltaic panels meets the design requirements, thereby improving the efficiency and accuracy of angle determination.

[0084] Example 3

[0085] Figure 7 This is a schematic diagram of a photovoltaic panel installation angle evaluation device provided in an embodiment of the present invention. This embodiment is applicable to situations where the installation angle of a photovoltaic panel is evaluated. The photovoltaic panel installation angle evaluation device can be implemented in hardware and / or software, and can be configured in any electronic device with network communication capabilities. Figure 7 As shown, the photovoltaic panel installation angle evaluation device of the present invention may include:

[0086] The information determination module 310 is used to determine the first point cloud data of the target photovoltaic panel and determine the outline boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together.

[0087] The point cloud data acquisition module 320 is used to divide the target photovoltaic panel into multiple grid blocks based on the contour boundary information, and acquire the second point cloud data of each grid block;

[0088] The vector determination module 330 is used to determine a first vector of the grid block based on the second point cloud data; the first vector is perpendicular to the grid block and points upward.

[0089] Evaluation module 340 is used to determine the angle information of the grid block based on the first vector and the second vector, and to evaluate the installation angle of the target photovoltaic panel based on the angle information of all the grid blocks; the second vector is the normal vector of the horizontal plane.

[0090] Based on the above embodiments, optionally, the information determination module is used to: acquire third point cloud data of a photovoltaic power station; the photovoltaic power station is equipped with multiple target photovoltaic panels; preprocess the third point cloud data to obtain fourth point cloud data; the preprocessing includes at least one of isolated point deletion and data filtering operations on the first coordinate axis; the first coordinate axis is perpendicular to the ground; perform point cloud segmentation on the fourth point cloud data based on a clustering algorithm to obtain point cloud regions corresponding to multiple target photovoltaic panels, and determine the point cloud data of the point cloud regions corresponding to the target photovoltaic panels as the first point cloud data of the target photovoltaic panels.

[0091] Based on the above embodiments, optionally, the point cloud data acquisition module includes a grid block division unit, which is used to construct a first covariance matrix of the first point cloud data, determine multiple first eigenvalues ​​of the first covariance matrix and first eigenvectors corresponding to the first eigenvalues; determine the direction of the first eigenvector corresponding to the largest first eigenvalue as a first direction, and determine the direction perpendicular to the first direction and parallel to the target photovoltaic panel as a second direction; and divide the target photovoltaic panel into multiple grid blocks based on the first direction, the second direction and the contour boundary information.

[0092] Based on the above embodiments, optionally, the contour boundary information includes the length information and width information of the target photovoltaic panel; the grid block division unit is further configured to: determine the size information of the grid block based on the length information and width information; and divide the target photovoltaic panel into multiple grid blocks along the first direction and the second direction based on the size information.

[0093] Based on the above embodiments, optionally, the vector determination module is used to: construct a second covariance matrix of the second point cloud data, determine multiple second eigenvalues ​​of the second covariance matrix and second eigenvectors corresponding to the second eigenvalues; and determine the second eigenvector corresponding to the smallest second eigenvalue among the second eigenvalues ​​as the first vector of the grid block.

[0094] Based on the above embodiments, optionally, the evaluation module includes an angle determination unit, which is used to: determine the target angle between the first vector and the second vector, and determine the remainder of the target angle as the angle information of the grid block.

[0095] Based on the above embodiments, optionally, the evaluation module is configured to generate an angle distribution map of the target photovoltaic panel based on the angle information of all the grid blocks; determine a target average value of the angle information of all the grid blocks, and determine the target average value as the predicted installation angle of the target photovoltaic panel; and evaluate the installation angle of the target photovoltaic panel based on the angle distribution map and the predicted installation angle.

[0096] The photovoltaic panel installation angle evaluation device provided in this embodiment of the invention can execute the photovoltaic panel installation angle evaluation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the method.

[0097] Example 4

[0098] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0099] Figure 8 A schematic diagram of an electronic device is shown that can be used to implement the method for evaluating the installation angle of a photovoltaic panel according to embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, 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.

[0100] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0101] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0102] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 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 11 performs the various methods and processes described above, such as the method for evaluating the installation angle of photovoltaic panels.

[0103] In some embodiments, the method for evaluating the photovoltaic panel mounting angle can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of the photovoltaic panel mounting angle evaluation method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the photovoltaic panel mounting angle evaluation method by any other suitable means (e.g., by means of firmware).

[0104] 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), system-on-a-chip (SoCs), complex 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.

[0105] 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.

[0106] 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.

[0107] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0108] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0109] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0110] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0111] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for evaluating the installation angle of a photovoltaic panel, characterized by, The method comprises: determining first point cloud data of a target photovoltaic panel, determining contour boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is spliced by a plurality of photovoltaic components; based on the contour boundary information, the target photovoltaic panel is divided into a plurality of grid blocks, and second point cloud data of each grid block is obtained; based on the second point cloud data, a first vector of the grid block is determined; the first vector is perpendicular to the grid block and the direction points upward; based on the first vector and the second vector, angle information of the grid block is determined, and the installation angle of the target photovoltaic panel is evaluated based on the angle information of all the grid blocks; the second vector is the normal vector of the horizontal plane.

2. The method of claim 1, wherein, The method comprises: obtaining third point cloud data of a photovoltaic power station; the photovoltaic power station is paved with a plurality of target photovoltaic panels; preprocessing the third point cloud data to obtain fourth point cloud data; the preprocessing at least includes any one of the data filtering operation of the first coordinate axis and the isolated point deletion; the first coordinate axis is perpendicular to the ground; based on a clustering algorithm, the fourth point cloud data is segmented to obtain a plurality of point cloud regions corresponding to the target photovoltaic panel, and the point cloud data of the point cloud region corresponding to the target photovoltaic panel is determined as the first point cloud data of the target photovoltaic panel.

3. The method of claim 1, wherein, The method comprises: constructing a first covariance matrix of the first point cloud data, determining a plurality of first eigenvalues of the first covariance matrix and a first eigenvector corresponding to the first eigenvalue; determining the direction of the first eigenvector corresponding to the largest first eigenvalue in the first eigenvalue as the first direction, and determining the direction perpendicular to the first direction and parallel to the target photovoltaic panel as the second direction; based on the first direction, the second direction and the contour boundary information, the target photovoltaic panel is divided into a plurality of grid blocks.

4. The method of claim 3, wherein, The contour boundary information includes length information and width information of the target photovoltaic panel; based on the first direction, the second direction and the contour boundary information, the target photovoltaic panel is divided into a plurality of grid blocks, comprising: based on the length information and width information, the size information of the grid block is determined; based on the size information, the target photovoltaic panel is divided into a plurality of grid blocks along the first direction and the second direction.

5. The method according to any one of claims 1 to 4, characterized in that, The method comprises: constructing a second covariance matrix of the second point cloud data, determining a plurality of second eigenvalues of the second covariance matrix and a second eigenvector corresponding to the second eigenvalue; determining the second eigenvector corresponding to the minimum second eigenvalue in the second eigenvalue as the first vector of the grid block.

6. The method of claim 5, wherein, The method comprises: determining the target included angle between the first vector and the second vector, and determining the result of the target included angle as the angle information of the grid block.

7. The method according to any one of claims 1 to 4, characterized in that, The evaluation of the installation angle of the target photovoltaic panel based on the angle information of all the grid blocks comprises: generating an angle distribution map of the target photovoltaic panel based on the angle information of all the grid blocks; determining a target average value of the angle information of all the grid blocks, and determining the target average value as a predicted installation angle of the target photovoltaic panel; evaluating the installation angle of the target photovoltaic panel based on the angle distribution map and the predicted installation angle.

8. An apparatus for evaluating the installation angle of a photovoltaic panel, characterized by The device comprises: an information determination module configured to determine first point cloud data of a target photovoltaic panel, and determine contour boundary information of the target photovoltaic panel based on the first point cloud data; the target photovoltaic panel is composed of a plurality of photovoltaic components; a point cloud data acquisition module configured to divide the target photovoltaic panel into a plurality of grid blocks based on the contour boundary information, and acquire second point cloud data of each grid block; a vector determination module configured to determine a first vector of the grid block based on the second point cloud data; the first vector is perpendicular to the grid block and points upward; an evaluation module configured to determine angle information of the grid block based on the first vector and a second vector, and evaluate an installation angle of the target photovoltaic panel based on the angle information of all the grid blocks; the second vector is a normal vector of a horizontal plane.

9. An electronic device, comprising: The electronic device comprises: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the evaluation method of the installation angle of the photovoltaic panel according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the evaluation method of the installation angle of the photovoltaic panel according to any one of claims 1-7 when executed.

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