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 a target center line and a first vector based on the first point cloud data; the first vector is a vector parallel to the target center line; determining a preset number of first analysis points on the target center line, determining the first analysis point adjacent to the second analysis point as a third analysis point, and extracting second point cloud data from the first point cloud data based on the distance between the second analysis point and the third analysis point; determining a second vector of the second analysis point based on the second point cloud data; and angle information corresponding to the second analysis points is determined based on the first vectors and the second vectors, and the installation angle of the target photovoltaic panel is evaluated based on the angle information corresponding to all the second analysis points. The problems that photovoltaic panel angle measurement needs manual field measurement, the efficiency is low, and the precision is limited are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy, and in particular to a method and device for evaluating the installation angle of a photovoltaic panel, and a storage medium. BACKGROUND

[0002] Photovoltaic power generation is an emerging renewable energy generation technology, and as an important component of new energy, it has been widely concerned and promoted. In a photovoltaic power generation system, the installation angle of a photovoltaic panel is one of the important factors in the fields of photovoltaic power station operation and management, solar resource assessment, and photovoltaic system design optimization. Traditional methods for measuring the installation angle of a photovoltaic panel mainly rely on manual measurement or the use of professional equipment, which is time-consuming and labor-intensive, has poor determination process efficiency, and is greatly affected by human factors, which greatly affects the accuracy of the determined installation angle of the photovoltaic panel. SUMMARY

[0003] The present application provides a method and device for evaluating the installation angle of a photovoltaic panel, and a storage medium, to solve the problems of manual field measurement, low efficiency, and limited accuracy in measuring the angle of a photovoltaic panel.

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

[0005] determining first point cloud data of a target photovoltaic panel, and determining a target center line and a first vector based on the first point cloud data; wherein the target photovoltaic panel is composed of a plurality of photovoltaic components; the target center line is a line segment passing through the center point of the target photovoltaic panel and parallel to a target edge of the target photovoltaic panel; the target edge is the longest edge of the target photovoltaic panel; and the first vector is the direction vector of the target center line;

[0006] determining a predetermined number of first analysis points on the target center line, determining a third analysis point adjacent to a second analysis point among the first analysis points, and extracting second point cloud data from the first point cloud data based on the distance between the second analysis point and the third analysis point; wherein the second analysis point is any one of the first analysis points;

[0007] determining a second vector of the second analysis point based on the second point cloud data; the second vector is perpendicular to a local photovoltaic panel and points upward in direction; and the local photovoltaic panel is the local position of the second analysis point on the target photovoltaic panel;

[0008] determining angle information corresponding to the second analysis point based on the first vector and the second vector, and evaluating the installation angle of the target photovoltaic panel based on the angle information corresponding to all the second analysis points.

[0009] According to another aspect of the present application, there is provided an apparatus for evaluating installation angle of a photovoltaic panel, the apparatus comprising:

[0010] an information determining module configured to determine first point cloud data of a target photovoltaic panel, determine a target center line and a first vector based on the first point cloud data, wherein the target photovoltaic panel is spliced by a plurality of photovoltaic components, the target center line is a line segment passing through a center point of the target photovoltaic panel and parallel to a target edge of the target photovoltaic panel, the target edge is the longest edge of the target photovoltaic panel, and the first vector is a direction vector of the target center line;

[0011] a data extracting module configured to determine a preset number of first analysis points on the target center line, determine a third analysis point based on a first analysis point adjacent to a second analysis point, and extract second point cloud data from the first point cloud data based on a distance between the second analysis point and the third analysis point, wherein the second analysis point is any one of the first analysis points;

[0012] a vector determining module configured to determine a second vector of the second analysis point based on the second point cloud data, wherein the second vector is perpendicular to a local photovoltaic panel and points upward, and the local photovoltaic panel is a local position corresponding to the second analysis point on the target photovoltaic panel;

[0013] an evaluation module configured to determine angle information corresponding to the second analysis point based on the first vector and the second vector, and evaluate installation angle of the target photovoltaic panel based on angle information corresponding to all the second analysis points.

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

[0015] at least one processor; and

[0016] a memory connected to the at least one processor in communication; wherein

[0017] 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 the embodiments of the present application.

[0018] According to another aspect of the present application, there is provided a computer readable storage medium storing computer instructions for enabling a processor to implement the evaluation method of the installation angle of the photovoltaic panel according to any one of the embodiments of the present application when executed by the processor.

[0019] The technical scheme of the embodiment of the present application determines the first point cloud data of a target photovoltaic panel spliced by a plurality of photovoltaic components, determines a target center line and a first vector parallel to the target center line based on the first point cloud data; so as to determine a preset number of first analysis points on the target center line, each point can be independently analyzed and fitted, and error accumulation of overall fitting is avoided; then a first analysis point adjacent to a second analysis point is determined as a third analysis point, second point cloud data is extracted from the first point cloud data based on the distance between the second analysis point and the third analysis point; the second analysis point is any one of the first analysis points; by analyzing the distance between the second analysis point and the third analysis point, the second point cloud data corresponding to the second analysis point can be more accurately extracted, so that the second vector of the second analysis point can be accurately determined based on the second point cloud data; the second vector is perpendicular to a local photovoltaic panel, and the direction points upward; the local photovoltaic panel is a local position corresponding to the second analysis point on the target photovoltaic panel; further, the angle information corresponding to the second analysis point is determined based on the first vector and the second vector, so as to evaluate the installation angle of the target photovoltaic panel based on the angle information corresponding to all the second analysis points, solve the problems of low efficiency and limited precision caused by manual on-site measurement for photovoltaic panel angle measurement, and improve the efficiency and accuracy of angle determination.

[0020] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent from the following description. BRIEF DESCRIPTION OF DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0022] Figure 1 is a flow chart of a photovoltaic panel installation angle evaluation method according to an embodiment of the present application;

[0023] Figure 2 is a schematic diagram of a target center line of a target photovoltaic panel and a first analysis point according to an embodiment of the present application;

[0024] Figure 3 is a schematic diagram of a first vector, a second vector and a third vector according to an embodiment of the present application;

[0025] Figure 4 is a flow chart of another method for evaluating installation angle of photovoltaic panel according to an embodiment of the present application;

[0026] Figure 5 is a schematic diagram of an angle distribution map of a target photovoltaic panel according to an embodiment of the present application;

[0027] Figure 6 is a structural schematic diagram of an evaluation device for installation angle of photovoltaic panel according to an embodiment of the present application;

[0028] Figure 7 is a structural schematic diagram of an electronic device for implementing the method for evaluating installation angle of photovoltaic panel according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0031] Embodiment one

[0032] Figure 1 A flow chart of a method for evaluating installation angle of photovoltaic panel according to an embodiment of the present application is provided, the present embodiment can be applicable to the case of evaluating installation angle of photovoltaic panel, the method can be executed by an evaluation device for installation angle of photovoltaic panel, the evaluation device for installation angle of photovoltaic panel can be realized in the form of hardware and / or software, and the evaluation device for installation angle of photovoltaic panel can be configured in any electronic device with network communication function. As shown in the figure, the method for evaluating installation angle of photovoltaic panel according to the present application can include: Figure 1 ​

[0033] S110. Determine the first point cloud data of the target photovoltaic panel, and determine the target centerline and the first vector based on the first point cloud data; wherein, the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together; the target centerline is a line segment passing through the center point of the target photovoltaic panel and parallel to the target edge of the target photovoltaic panel; the target edge is the longest edge of the target photovoltaic panel; the first vector is the direction vector of the target centerline.

[0034] The first point cloud data is 3D point cloud data. The two ends of the target centerline are connected to the edges of the target photovoltaic panel; these connecting edges are generally the wide edges of the target photovoltaic panel, i.e., edges perpendicular to the target. For example, as shown... Figure 2 The target centerline of the target photovoltaic panel is shown. Figure 3 The diagram shows a schematic of using the direction vector of the target centerline as the first vector.

[0035] Specifically, point cloud preprocessing is performed on the first point cloud data to obtain preprocessed first point cloud data, thereby reducing computational load and avoiding fitting bias. Further, the centroid of the target photovoltaic panel's point cloud is determined based on the preprocessed first point cloud data. Then, a reference line segment passing through the centroid of the point cloud and intersecting with the edge of the target photovoltaic panel is fitted based on the preprocessed first point cloud data, and the longest reference line segment is taken as the target centerline.

[0036] Optionally, in an embodiment of the present invention, determining the target centerline and the first vector based on the first point cloud data includes: constructing a first covariance matrix of the first point cloud data; determining multiple first eigenvalues ​​of the first covariance matrix and the first eigenvectors corresponding to the first eigenvalues; determining the first eigenvector corresponding to the largest first eigenvalue as the first vector; determining the center point of the target photovoltaic panel based on the first point cloud data; determining the line segment passing through the center point of the target photovoltaic panel and parallel to the first vector as the target centerline; and connecting the two ends of the target centerline to the edges of the target photovoltaic panel.

[0037] In an embodiment of the present invention, optionally, determining the first point cloud data of the target photovoltaic panel may include steps A1-A3:

[0038] Step A1: Obtain the third-point cloud data of the photovoltaic power station; the photovoltaic power station has multiple target photovoltaic panels.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] Step A3: Perform point cloud segmentation on the fourth point cloud data based on 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.

[0044] The clustering algorithm can be either density-based spatial clustering (DBSCAN) or K-means clustering.

[0045] 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.

[0046] 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.

[0047] S120. Determine a preset number of first analysis points on the target centerline, and determine the first analysis point adjacent to the second analysis point as the third analysis point. Based on the distance between the second analysis point and the third analysis point, extract the second point cloud data from the first point cloud data; wherein, the second analysis point is any one of the first analysis points.

[0048] Specifically, the distance between the first analysis points can be either unequally spaced or equally spaced. For example, ... Figure 2 As shown, the first analysis points are divided at equal intervals. Extracting second point cloud data from the first point cloud data based on the distance between the second and third analysis points can include: extracting first point cloud data at a preset reference distance from the second analysis point, and defining this as the second point cloud data. The preset reference distance can be half the distance between the second and third analysis points.

[0049] S130. Based on the second point cloud data, determine the second vector of the second analysis point; the second vector is perpendicular to the local photovoltaic panel and points upward; the local photovoltaic panel is the local position of the second analysis point on the target photovoltaic panel.

[0050] Specifically, the second point cloud data is fitted to a plane using the least squares method to obtain the plane equation corresponding to the second analysis point. The normal vector obtained by solving the plane equation corresponding to the second analysis point is then used as the second vector of the second analysis point. For example... Figure 3 The diagram shows a second vector perpendicular to a local photovoltaic panel and pointing upwards.

[0051] Optionally, determining the second vector of the second analysis point 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 second vector of the second analysis point.

[0052] S140. Based on the first vector and the second vector, determine the angle information corresponding to the second analysis point. Based on the angle information corresponding to all the second analysis points, evaluate the installation angle of the target photovoltaic panel.

[0053] Specifically, the angle information corresponding to the second analysis point is the angle between the local panel on the target photovoltaic panel corresponding to the second analysis point and the horizontal plane. The angle information corresponding to all the second analysis points can reflect the angle between the multiple local panels of the target photovoltaic panel and the horizontal plane, thus effectively reflecting the local deformation or uneven installation of the panel.

[0054] Determining the angle information corresponding to the second analysis point based on the first vector and the second vector may include: obtaining the third vector corresponding to the perpendicular segment of the second analysis point by performing a cross product operation on the first vector and the second vector; the perpendicular segment is a line segment that passes through the analysis point and is perpendicular to the target centerline; and determining the angle between the third vector and the horizontal plane as the angle information corresponding to the second analysis point.

[0055] The technical solution of this invention involves determining first point cloud data of a target photovoltaic panel composed of multiple photovoltaic modules, and determining a target centerline and a first vector parallel to the target centerline based on the first point cloud data. This facilitates the determination of a preset number of first analysis points on the target centerline, each of which can be analyzed and fitted independently, avoiding the accumulation of errors in the overall fitting. Then, the first analysis point adjacent to the second analysis point is determined as the third analysis point. Based on the distance between the second and third analysis points, second point cloud data is extracted from the first point cloud data. The second analysis point can be any one of the first analysis points. By analyzing the distance between the second and third analysis points, the second point cloud corresponding to the second analysis point can be extracted more accurately. The data ensures that the second vector of the second analysis point can be accurately determined based on the second point cloud data; the second vector is perpendicular to the local photovoltaic panel and points upward; the local photovoltaic panel is the local position of the second analysis point on the target photovoltaic panel; further, the angle information corresponding to the second analysis point is determined based on the first and second vectors, so as to evaluate the installation angle of the target photovoltaic panel based on the angle information corresponding to all the second analysis points, solving the problems of low efficiency and limited accuracy of photovoltaic panel angle measurement requiring manual on-site measurement. The angle information corresponding to all the second analysis points can also be used to evaluate the installation angle of the target photovoltaic panel, and can also identify local deformation or uneven installation of the panel, improving the efficiency and accuracy of angle determination.

[0056] Example 2

[0057] 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:

[0058] S210. Determine the first point cloud data of the target photovoltaic panel, and determine the target centerline and the first vector based on the first point cloud data; wherein, the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together; the target centerline is a line segment passing through the center point of the target photovoltaic panel and parallel to the target edge of the target photovoltaic panel; the target edge is the longest edge of the target photovoltaic panel; the first vector is the direction vector of the target centerline.

[0059] S220. Determine a preset number of first analysis points on the target centerline, and determine the first analysis point adjacent to the second analysis point as the third analysis point, wherein the second analysis point is any one of the first analysis points.

[0060] S230. If the distance between the second analysis point and the third analysis point is less than the first preset distance, then the data extraction radius is determined to be the first radius.

[0061] Wherein, the first radius is smaller than the first preset distance. For example, the first preset distance is 0.4 meters and the first radius is 0.2 meters.

[0062] S240. If the distance between the second analysis point and the third analysis point is greater than the second preset distance, then the data extraction radius is determined to be the second radius; the second preset distance is greater than the first preset distance; the second radius is greater than the first radius.

[0063] The second radius is smaller than the second preset distance. For example, the second preset distance is 1.2 meters and the first radius is 0.6 meters.

[0064] S250. If the distance between the second analysis point and the third analysis point is between the first preset distance and the second preset distance, then the data extraction radius is determined to be the third radius; the third radius is half the distance between the second analysis point and the third analysis point.

[0065] S260. Based on the data extraction radius and the second analysis point, extract the second point cloud data from the first point cloud data.

[0066] Specifically, the perpendicular segment to the second analysis point is determined. The first point cloud data within the data extraction radius, at a distance equal to the distance of the perpendicular segment from the second analysis point, is extracted to obtain the second point cloud data. The perpendicular segment is a line segment passing through the analysis point and perpendicular to the target centerline.

[0067] S270. Based on the second point cloud data, determine the second vector of the second analysis point; the second vector is perpendicular to the local photovoltaic panel and points upward; the local photovoltaic panel is the local position of the second analysis point on the target photovoltaic panel.

[0068] S280. The first vector and the second vector are multiplied by a cross product to obtain the third vector corresponding to the perpendicular segment of the second analysis point; the perpendicular segment is a line segment that passes through the analysis point and is perpendicular to the target center line; the angle between the third vector and the horizontal plane is determined as the angle information corresponding to the second analysis point.

[0069] For example, such as Figure 3 The diagram shows a third vector corresponding to the perpendicular segment of the second analysis point, obtained by performing a cross product operation on the first and second vectors.

[0070] S290. Based on the angle information corresponding to all second analysis points, evaluate the installation angle of the target photovoltaic panel.

[0071] Specifically, based on the angle information corresponding to all second analysis points, evaluating the installation angle of the target photovoltaic panel may include steps B1-B3:

[0072] Step B1: Generate an angle distribution map of the target photovoltaic panel based on the angle information corresponding to all second analysis points.

[0073] Specifically, based on the location and angle information of each second analysis point, an angle distribution map of the target photovoltaic panel is generated, such as... Figure 5 This shows the distribution of angular information for all second analysis points in the target photovoltaic panel.

[0074] Step B2: Determine the target average value of the angle information corresponding to all second analysis points, and use the target average value as the predicted installation angle of the target photovoltaic panel;

[0075] Step B3: Based on the angle distribution map and the predicted installation angle, evaluate the installation angle of the target photovoltaic panel.

[0076] Specifically, a photovoltaic panel is considered qualified if its installation angle falls within a preset angle range. Predicting the installation angle provides a rough overall indication of whether the target photovoltaic panel's installation angle meets requirements. The installation angle of each second analysis point should also fall within a preset angle range. If the number of second analysis points with angles outside the preset range exceeds the preset number, there is a problem with the installation of the target photovoltaic panel. The angle distribution diagram also provides a more intuitive way to pinpoint which local areas of the target photovoltaic panel are problematic, allowing for faster adjustments. This approach not only estimates the overall angle but also identifies localized panel deformation and uneven installation, providing more comprehensive quality assessment information.

[0077] Furthermore, based on the angle distribution map, predicted installation angles, and the location information of each target photovoltaic panel, along with the first point cloud data, each target photovoltaic panel in the photovoltaic power station can be displayed in 3D visualization. Text labels are added to the angle information of each target photovoltaic panel, displaying the precise predicted installation angle at the center of the panel, and the angle information of the second analysis point is displayed at local locations corresponding to the second analysis point. The visualization interface supports adjustment of point cloud rendering parameters, including point size, background color, and text depth. In this embodiment, the point size can be set to 3.0 pixels, the background color can be light gray (RGB:0.9,0.9,0.9), and the text depth can be 0.01 meters to ensure clear and visible angle labels. This enables an intuitive display of the spatial distribution of photovoltaic panels and angle measurement results.

[0078] 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.

[0079] 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.

[0080] 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.

[0081] 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.

[0082] 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.

[0083] 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.

[0084] 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.

[0085] The technical solution of this invention involves determining first point cloud data of a target photovoltaic panel, and determining a target centerline and a first vector based on the first point cloud data. The target photovoltaic panel is composed of multiple photovoltaic modules. The target centerline is a line segment passing through the center point of the target photovoltaic panel and parallel to its long side. The first vector is the direction vector of the target centerline. A predetermined number of first analysis points are determined on the target centerline. A third analysis point is determined from the first analysis points adjacent to the second analysis points. The second analysis point is any one of the first analysis points. By analyzing the distance between the second and third analysis points, the data extraction radius is accurately determined, ensuring the accuracy of the second point cloud data extracted from the first point cloud data based on the data extraction radius and the second analysis points. Further, based on the second point cloud data, a second vector of the second analysis point is determined. The second vector is perpendicular to the local photovoltaic panel and points upwards. The local photovoltaic panel is the local position of the second analysis point on the target photovoltaic surface. The first and second vectors are multiplied by a cross product to obtain the third vector corresponding to the perpendicular segment of the second analysis point. The perpendicular segment is a line segment that passes through the analysis point and is perpendicular to the target centerline. The angle between the third vector and the horizontal plane is determined as the angle information corresponding to the second analysis point. This allows for the evaluation of the installation angle of the target photovoltaic panel based on the angle information corresponding to all second analysis points. This solves the problems of low efficiency and limited accuracy in photovoltaic panel angle measurement, which requires manual on-site measurement. Evaluating the installation angle of the target photovoltaic panel using the angle information corresponding to all second analysis points can also identify local deformation or uneven installation of the panel, improving the efficiency and accuracy of angle determination.

[0086] Example 3

[0087] Figure 6 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 6 As shown, the evaluation device for the installation angle of photovoltaic panels includes:

[0088] Information determination module 310 is used to determine the first point cloud data of the target photovoltaic panel, and determine the target centerline and the first vector based on the first point cloud data; wherein, the target photovoltaic panel is composed of multiple photovoltaic modules spliced ​​together; the target centerline is a line segment passing through the center point of the target photovoltaic panel and parallel to the target edge of the target photovoltaic panel; the target edge is the longest edge of the target photovoltaic panel; the first vector is the direction vector of the target centerline;

[0089] The data extraction module 320 is used to determine a preset number of first analysis points on the target center line, determine the first analysis points adjacent to the second analysis points as third analysis points, and extract second point cloud data from the first point cloud data based on the distance between the second analysis point and the third analysis point; wherein, the second analysis point is any one of the first analysis points;

[0090] The vector determination module 330 is used to determine a second vector of the second analysis point based on the second point cloud data; the second vector is perpendicular to the local photovoltaic panel and points upward; the local photovoltaic panel is the local position of the second analysis point on the target photovoltaic panel;

[0091] The evaluation module 340 is used to determine the angle information corresponding to the second analysis point 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 corresponding to all the second analysis points.

[0092] Based on the above embodiments, optionally, the information determination module includes a point cloud data determination unit, which 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.

[0093] Based on the above embodiments, optionally, the information determination module includes an information determination 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 first eigenvector corresponding to the largest first eigenvalue among the first eigenvalues ​​as a first vector; determine the center point of the target photovoltaic panel based on the first point cloud data; determine the line segment passing through the center point of the target photovoltaic panel and parallel to the first vector as the target centerline; and connect the two ends of the target centerline to the edges of the target photovoltaic panel.

[0094] Based on the above embodiments, optionally, the data extraction module is configured to: determine a data extraction radius as a first radius if the distance between the second analysis point and the third analysis point is less than a first preset distance; determine a data extraction radius as a second radius if the distance between the second analysis point and the third analysis point is greater than a second preset distance; the second preset distance is greater than the first preset distance; the second radius is greater than the first radius; if the distance between the second analysis point and the third analysis point is between the first preset distance and the second preset distance, determine a data extraction radius as a third radius; the third radius is half the distance between the second analysis point and the third analysis point; and extract second point cloud data from the first point cloud data based on the data extraction radius and the second analysis point.

[0095] 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 the second eigenvectors corresponding to the second eigenvalues; and determine the second eigenvector corresponding to the smallest second eigenvalue among the second eigenvalues ​​as the second vector of the second analysis point.

[0096] Based on the above embodiments, optionally, the evaluation module includes an angle information determination unit, which is used to: obtain a third vector corresponding to the perpendicular segment of the second analysis point by performing a vector cross product operation on the first vector and the second vector; the perpendicular segment is a line segment that passes through the analysis point and is perpendicular to the target center line; and determine the angle between the third vector and the horizontal plane as the angle information corresponding to the second analysis point.

[0097] Based on the above embodiments, optionally, the evaluation module includes an evaluation unit, which is configured to: generate an angle distribution map of the target photovoltaic panel based on the angle information corresponding to all the second analysis points; determine the target average value of the angle information corresponding to all the second analysis points, 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.

[0098] 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.

[0099] Example 4

[0100] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0101] Figure 7 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.

[0102] like Figure 7 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.

[0103] 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.

[0104] 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.

[0105] 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).

[0106] 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.

[0107] 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.

[0108] 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.

[0109] 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).

[0110] 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.

[0111] 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.

[0112] 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.

[0113] 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 a target center line and a first vector based on the first point cloud data; wherein the target photovoltaic panel is spliced by a plurality of photovoltaic components; the target center line is a line segment passing through a center point of the target photovoltaic panel and parallel to a target edge of the target photovoltaic panel; the target edge is the longest edge of the target photovoltaic panel; the first vector is a directional vector of the target center line; determining a preset number of first analysis points on the target center line, determining a third analysis point adjacent to a second analysis point among the first analysis points, and extracting second point cloud data from the first point cloud data based on a distance between the second analysis point and the third analysis point; wherein the second analysis point is any one of the first analysis points; determining a second vector of the second analysis point based on the second point cloud data; the second vector is perpendicular to a local photovoltaic panel and points upward; the local photovoltaic panel is a local position corresponding to the second analysis point on the target photovoltaic panel; determining angle information corresponding to the second analysis point based on the first vector and the second vector, and evaluating an installation angle of the target photovoltaic panel based on angle information corresponding to all the second analysis points.

2. 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 first eigenvectors corresponding to the first eigenvalues; determining a first eigenvector corresponding to a largest first eigenvalue in the first eigenvalues as the first vector; determining a center point of the target photovoltaic panel based on the first point cloud data; determining a line segment passing through the center point of the target photovoltaic panel and parallel to the first vector as the target center line; the target center line is connected to an edge of the target photovoltaic panel at both ends.

3. The method of claim 1, wherein, The method comprises: if the distance between the second analysis point and the third analysis point is less than a first preset distance, determining a data extraction radius as a first radius; if the distance between the second analysis point and the third analysis point is greater than a second preset distance, determining a data extraction radius as a second radius; the second preset distance is greater than the first preset distance; the second radius is greater than the first radius; if the distance between the second analysis point and the third analysis point is between the first preset distance and the second preset distance, determining a data extraction radius as a third radius; the third radius is half of the distance between the second analysis point and the third analysis point; extracting second point cloud data from the first point cloud data based on the data extraction radius and the second analysis point.

4. The method of claim 1, wherein, 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 second eigenvectors corresponding to the second eigenvalues; The second eigenvector corresponding to the minimum second eigenvalue in the second eigenvalues is determined as a second vector of the second analysis point.

5. The method of claim 1, wherein, The angle information corresponding to the second analysis point is determined based on the first vector and the second vector, including: The first vector and the second vector are subjected to vector cross multiplication operation to obtain a third vector corresponding to a perpendicular segment of the second analysis point; the perpendicular segment is a line segment passing through the analysis point and perpendicular to the target center line; The angle between the third vector and the horizontal plane is determined as the angle information corresponding to the second analysis point.

6. The method of claim 5, wherein, The installation angle of the target photovoltaic panel is evaluated based on the angle information corresponding to all the second analysis points, including: An angle distribution map of the target photovoltaic panel is generated based on the angle information corresponding to all the second analysis points; A target average value of the angle information corresponding to all the second analysis points is determined, and the target average value is determined as a predicted installation angle of the target photovoltaic panel; The installation angle of the target photovoltaic panel is evaluated based on the angle distribution map and the predicted installation angle.

7. The method according to any one of claims 1 to 6, characterized in that, The first point cloud data of the target photovoltaic panel is determined, including: Third point cloud data of a photovoltaic power station is obtained; the photovoltaic power station is paved with a plurality of target photovoltaic panels; The third point cloud data is preprocessed to obtain fourth point cloud data; the preprocessing at least includes any one of isolated point deletion and data filtering operation of a first coordinate axis; the first coordinate axis is perpendicular to the ground; Point cloud segmentation is performed on the fourth point cloud data based on a clustering algorithm to obtain a plurality of point cloud regions corresponding to the target photovoltaic panels, and 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.

8. An apparatus for evaluating the installation angle of a photovoltaic panel, characterized by The device includes: An information determination module is configured to determine first point cloud data of a target photovoltaic panel, and determine a target center line and a first vector based on the first point cloud data; wherein the target photovoltaic panel is spliced by a plurality of photovoltaic components; the target center line is a line segment passing through a center point of the target photovoltaic panel and parallel to a target edge of the target photovoltaic panel; the target edge is the longest edge of the target photovoltaic panel; and the first vector is a direction vector of the target center line; A data extraction module is configured to determine a preset number of first analysis points on the target center line, determine a third analysis point based on a first analysis point adjacent to a second analysis point, and extract second point cloud data from the first point cloud data based on a distance between the second analysis point and the third analysis point; wherein the second analysis point is any one of the first analysis points; A vector determination module is configured to determine a second vector of the second analysis point based on the second point cloud data; the second vector is perpendicular to a local photovoltaic panel and points upward in direction; and the local photovoltaic panel is a local position of the second analysis point on the target photovoltaic panel; An evaluation module is configured to determine angle information corresponding to the second analysis point based on the first vector and the second vector, and evaluate an installation angle of the target photovoltaic panel based on the angle information corresponding to all the second analysis points.

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 method for evaluating 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 implement the method for evaluating the installation angle of the photovoltaic panel according to any one of claims 1-7 when executed.

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