Segmentation method of large-area tiled photovoltaic module and related device

Abstract

The invention discloses a large-area tiled photovoltaic module segmentation method and a related device, and belongs to the field of photovoltaic simulation analysis, and the method comprises the following steps: obtaining the vector information of a distributed photovoltaic roof according to the orthographic image data and point cloud data, and obtaining the total area of the distributed photovoltaic roof according to the vector information; latitude and longitude information and a solar altitude of the distributed photovoltaic roof are extracted, and a light irradiation direction is calculated according to the latitude and longitude information and the solar altitude; according to the total area of the distributed photovoltaic roof and the light irradiation direction, the shadow area of the distributed photovoltaic roof is obtained; and according to the total area and the shadow area of the distributed photovoltaic roof, obtaining the available area of the tiled photovoltaic modules, and combining the specifications of the tiled photovoltaic modules to obtain the theoretical laying number of the large-area tiled photovoltaic modules. The problem that an existing 2D segmentation method cannot process a large-area tiled photovoltaic module image can be solved.

Description

Technical Field

[0001] The invention belongs to the field of photovoltaic simulation analysis, and in particular relates to a segmentation method and a related device for a large-area flat photovoltaic assembly. Background Art

[0002] As the global demand for renewable energy continues to grow, distributed photovoltaic power generation has received widespread attention and application as a clean and efficient way of energy utilization. Especially in urban areas, roofs, as valuable available space, are used extensively to install photovoltaic modules to achieve green energy transformation. However, in practical applications, large-area flat-installed distributed photovoltaic roofs face the problem of dense components and inability to achieve 2D segmentation. Traditional photovoltaic module installation methods rely on precise 2D segmentation technology to ensure that each component can be accurately positioned during the installation process, thereby ensuring the overall performance and safety of the photovoltaic system. However, in large-area photovoltaic roof projects, due to the large number of components and their close arrangement, traditional 2D segmentation methods are often difficult to implement. This not only increases the difficulty of installation, but may also affect the power generation efficiency and safety of the photovoltaic system. Summary of the invention

[0003] The purpose of the present invention is to provide a segmentation method and related devices for large-area tiled photovoltaic modules, so as to solve the problem that the existing 2D segmentation method cannot process images of large-area tiled photovoltaic modules.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, a method for dividing a large-area tiled photovoltaic module comprises the following steps: Collect orthophoto data and point cloud data of tiled photovoltaic modules; Acquire vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtain the total area of ​​the distributed photovoltaic roof according to the vector information; Extracting the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof, and calculating the light irradiation direction according to the longitude and latitude information and the solar altitude angle; Obtaining the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the direction of light irradiation; The available area of ​​the tiled photovoltaic modules is obtained according to the total area and the shadow area of ​​the distributed photovoltaic roof, and the theoretical number of large-area tiled photovoltaic modules is obtained in combination with the specifications of the tiled photovoltaic modules to achieve segmentation.

[0005] In some embodiments, the step of acquiring vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtaining the total area of ​​the distributed photovoltaic roof according to the vector information specifically includes: According to the orthophoto image data and point cloud data, the vector information of the distributed photovoltaic roof is obtained by using the Unet convolutional neural network; The geometric features in the vector information are extracted, and the total area of ​​the distributed photovoltaic roof is calculated according to the geometric features.

[0006] In some embodiments, a building information model is used to extract the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof.

[0007] In some embodiments, the step of obtaining the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the light irradiation direction specifically includes: Combining the vector information with the light irradiation direction to obtain target vector information that generates shadow occlusion; A polygon union algorithm is adopted and combined with the target vector information that generates shadow occlusion and the area of ​​the distributed photovoltaic roof to obtain a shadow polygon union, and the shadow area of ​​the distributed photovoltaic roof is obtained based on the analysis of the shadow polygon union.

[0008] In some embodiments, the vector information of the distributed photovoltaic roof includes area, height, and side elevation area.

[0009] In some embodiments, the step of obtaining the available area of ​​the tiled photovoltaic modules according to the total area and the shadow area of ​​the distributed photovoltaic roof, and obtaining the theoretical number of large-area tiled photovoltaic modules in combination with the specifications of the tiled photovoltaic modules, specifically includes: The available area of ​​the tiled photovoltaic module is obtained by subtracting the shadow area from the total area; Calculate the optimal inclination angle and optimal spacing of the tiled photovoltaic modules installed on the distributed photovoltaic roof according to the specifications and available area of ​​the tiled photovoltaic modules; The theoretical number of large-area tiled photovoltaic modules to be laid is calculated based on the available area, optimal tilt angle and optimal spacing.

[0010] In a second aspect, a system for dividing a large-area tiled photovoltaic module includes: A data acquisition module, used to collect orthophoto data and point cloud data of tiled photovoltaic modules; An image segmentation module, used to obtain vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtain the total area of ​​the distributed photovoltaic roof according to the vector information; A light irradiation analysis module is used to extract the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof, and calculate the light irradiation direction according to the longitude and latitude information and the solar altitude angle; A shadow analysis module, used to obtain the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the direction of light exposure; The theoretical laying quantity calculation module is used to obtain the available area of ​​the flat-laid photovoltaic modules according to the total area and shadow area of ​​the distributed photovoltaic roof, and to obtain the theoretical laying quantity of large-area flat-laid photovoltaic modules in combination with the specifications of the flat-laid photovoltaic modules to achieve segmentation.

[0011] In a third aspect, a computer device includes a memory, a processor, and a computer program stored in the memory and executable in the processor, wherein the processor implements the steps of the method for dividing a large-area tiled photovoltaic module when executing the computer program.

[0012] In a fourth aspect, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for dividing a large-area tiled photovoltaic module are implemented.

[0013] A fifth aspect is a computer program product, which includes a computer program, characterized in that when the computer program is executed by a processor, the steps of the method for dividing the large-area tiled photovoltaic module are implemented.

[0014] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a segmentation method for large-area tiled photovoltaic modules. By collecting orthophoto image data and point cloud data of tiled photovoltaic modules, vector information of distributed photovoltaic roofs can be obtained more accurately, and the total area of ​​the roof can be accurately calculated. According to the direction of light irradiation and the shadow area, the available area of ​​the photovoltaic module can be accurately calculated, and the optimal inclination angle and optimal spacing can be calculated in combination with the specifications of the photovoltaic module, so as to optimize the layout of the photovoltaic module and improve the power generation efficiency. This method is not only suitable for photovoltaic roofs with regular shapes, but can also handle complex shapes and polygonal roofs, and has strong adaptability and flexibility. The present invention can solve the problem that the existing 2D segmentation method cannot handle large-area tiled photovoltaic module images.

[0015] Furthermore, the present invention utilizes the Unet convolutional neural network to process orthophoto data and point cloud data to improve the accuracy and efficiency of vector information extraction.

[0016] Furthermore, the present invention can automatically extract the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof in combination with the building information modeling (BIM), without manual measurement, thus improving work efficiency.

[0017] Furthermore, the present invention can accurately identify which parts of the photovoltaic roof will be shaded by combining vector information and light irradiation direction and using a polygon union algorithm. This method is more accurate than the traditional method based on simple geometric shapes or empirical estimation, and can take into account complex lighting conditions and roof shapes. Whether it is a regular shape or a complex polygonal roof, this method can obtain accurate shadow areas. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of a method for dividing a large-area tiled photovoltaic module provided in Example 1; Figure 2 This is a structural diagram of the segmentation system of the large-area tiled photovoltaic module provided in Example 2. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the solution of the present invention, the technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings, and the described content is intended to explain the present invention rather than to limit it.

[0020] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units that are not explicitly listed or are inherent to these processes, methods, systems, products or apparatus.

[0021] Embodiment 1 This embodiment adopts the method of overall large area segmentation to estimate the number of modules to be laid by area. The core idea of ​​this method is to regard the entire photovoltaic roof as a whole, and calculate the number of modules that can be laid theoretically based on the available area of ​​the roof and the specifications of the selected photovoltaic modules. Then, through flexible module arrangement and precise spacing setting, it is ensured that the photovoltaic system can efficiently receive sunlight and maximize power generation.

[0022] During implementation, this method also needs to consider a variety of factors, such as the shape, size and orientation of the roof, as well as shadowing issues. Therefore, it is crucial to optimize the layout of photovoltaic panels to ensure the stability and power generation efficiency of the system.

[0023] like Figure 1 As shown, a method for dividing a large-area flat photovoltaic module includes the following steps: S1, collects orthophoto data and point cloud data of tiled photovoltaic modules; Use drones or ground scanning equipment to take orthophoto images of the photovoltaic roof to obtain high-quality orthophoto image data, and use lidar to collect point cloud data of the photovoltaic roof, which contains the three-dimensional coordinate information of the roof surface.

[0024] S2, acquiring vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtaining the total area of ​​the distributed photovoltaic roof according to the vector information; According to the orthoimage data and the point cloud data, the Unet convolutional neural network is used to obtain vector information of the distributed photovoltaic roof, geometric features in the vector information are extracted, and the total area of ​​the distributed photovoltaic roof is calculated according to the geometric features; The vector information of the distributed photovoltaic roof includes area, height and side elevation area.

[0025] S3, using a building information model to extract the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof, and calculating the light irradiation direction according to the longitude and latitude information and the solar altitude angle; Building Information Modeling (BIM) is a digital expression of the physical and functional characteristics of a building. It can provide users with comprehensive and accurate building information, so BIM can be used for photovoltaic layout.

[0026] S4, obtaining the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the direction of light irradiation; Combining the vector information with the light irradiation direction to obtain target vector information that generates shadow occlusion; By adopting a polygon union algorithm and combining the target vector information of the shadow occlusion and the area of ​​the distributed photovoltaic roof, the shadow occlusion portion is extracted from the vector information of obstacles (such as buildings and trees) to form a shadow occlusion polygon.

[0027] The polygon union algorithm is a computational geometry algorithm used to calculate the union of two or more polygons. In this process, it is necessary to process geometric relationships such as the intersection points of polygons and the relative positions of edges.

[0028] The extracted shadow shading polygon is combined with the vector polygon of the distributed photovoltaic roof to obtain the shadow polygon union; According to the analysis of the union of shadow polygons, the area of ​​the union of shadow polygons is calculated using the vector product method to obtain the shadow area of ​​the distributed photovoltaic roof.

[0029] S5, obtaining the available area of ​​the tiled photovoltaic modules according to the total area and the shadow area of ​​the distributed photovoltaic roof, and obtaining the theoretical number of large-area tiled photovoltaic modules according to the specifications of the tiled photovoltaic modules to achieve segmentation.

[0030] The available area of ​​the tiled photovoltaic module is obtained by subtracting the shadow area from the total area; Calculate the optimal inclination angle and optimal spacing of the tiled photovoltaic modules installed on the distributed photovoltaic roof according to the specifications and available area of ​​the tiled photovoltaic modules; When calculating the best tilt angle and spacing, the tilt angle that allows the photovoltaic modules to receive the most solar radiation is calculated based on the solar radiation and the power generation efficiency of the photovoltaic modules. Considering the size of the photovoltaic modules, the local wind speed and direction, and the layout of the photovoltaic array (such as horizontal or vertical arrangement), the spacing that allows the photovoltaic modules to avoid blocking each other and achieve the best stability is calculated.

[0031] The theoretical number of large-area flat-laying photovoltaic modules is calculated based on the available area, optimal inclination angle and optimal spacing. Specifically, the floor area of ​​a single photovoltaic module on the roof is calculated based on the optimal spacing and optimal inclination angle of the photovoltaic modules, and then the available area is divided by the floor area of ​​a single photovoltaic module to obtain the theoretical number of photovoltaic modules that can be laid.

[0032] In summary, the method provided in this embodiment for dividing a large area and estimating the number of components to be laid by area provides an effective solution to the problem of dense distributed photovoltaic roof components installed in a large area. This method not only simplifies the installation process and improves installation efficiency, but also provides strong data support for the subsequent operation and maintenance management of the photovoltaic system.

[0033] Embodiment 2 like Figure 2 As shown, this embodiment provides a system for dividing a large-area tiled photovoltaic module, including: A data acquisition module, used to collect orthophoto data and point cloud data of tiled photovoltaic modules; An image segmentation module, used to obtain vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtain the total area of ​​the distributed photovoltaic roof according to the vector information; A light irradiation analysis module is used to extract the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof, and calculate the light irradiation direction according to the longitude and latitude information and the solar altitude angle; A shadow analysis module, used to obtain the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the direction of light exposure; The theoretical laying quantity calculation module is used to obtain the available area of ​​the flat-laid photovoltaic modules according to the total area and shadow area of ​​the distributed photovoltaic roof, and to obtain the theoretical laying quantity of large-area flat-laid photovoltaic modules in combination with the specifications of the flat-laid photovoltaic modules to achieve segmentation.

[0034] The division of modules in the embodiments of the present invention is schematic and is only a logical function division. There may be other division methods in actual implementation. In addition, each functional module in each embodiment of the present invention may be integrated into one processor, or may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0035] In this embodiment, a computer device is also provided, which includes a processor and a memory, the memory is used to store a computer program (in this embodiment, the computer program includes a computing component and an iterative component, which can perform model calculation and model update), the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of the segmentation method of large-area tiled photovoltaic modules.

[0036] This embodiment also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the method for segmenting large-area tiled photovoltaic modules in the above embodiment.

[0037] This embodiment further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the corresponding steps of the method for dividing a large-area tiled photovoltaic module in the above embodiment are implemented.

[0038] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0039] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0040] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0041] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0042] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A method for dividing a large-area tiled photovoltaic module, characterized in that: The following steps are involved: Collect orthophoto data and point cloud data of tiled photovoltaic modules; Acquire vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtain the total area of ​​the distributed photovoltaic roof according to the vector information; Extracting the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof, and calculating the light irradiation direction according to the longitude and latitude information and the solar altitude angle; Obtaining the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the direction of light irradiation; The available area of ​​the tiled photovoltaic modules is obtained according to the total area and the shadow area of ​​the distributed photovoltaic roof, and the theoretical number of large-area tiled photovoltaic modules is obtained in combination with the specifications of the tiled photovoltaic modules to achieve segmentation.

2. A method for dividing a large-area tiled photovoltaic module according to claim 1, characterized in that: The step of acquiring the vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtaining the total area of ​​the distributed photovoltaic roof according to the vector information, specifically includes: According to the orthophoto image data and point cloud data, the vector information of the distributed photovoltaic roof is obtained by using the Unet convolutional neural network; The geometric features in the vector information are extracted, and the total area of ​​the distributed photovoltaic roof is calculated according to the geometric features.

3. A method for dividing a large-area tiled photovoltaic module according to claim 1, characterized in that: The building information model is used to extract the longitude and latitude information and solar altitude angle of the distributed photovoltaic roof.

4. A method for dividing a large-area tiled photovoltaic module according to claim 1, characterized in that: The step of obtaining the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the light irradiation direction specifically includes: Combining the vector information with the light irradiation direction to obtain target vector information that generates shadow occlusion; A polygon union algorithm is adopted and combined with the target vector information that generates shadow occlusion and the area of ​​the distributed photovoltaic roof to obtain a shadow polygon union, and the shadow area of ​​the distributed photovoltaic roof is obtained based on the analysis of the shadow polygon union.

5. The method for dividing a large-area tiled photovoltaic module according to claim 1, characterized in that: The vector information of the distributed photovoltaic roof includes area, height and side elevation area.

6. A method for dividing a large-area tiled photovoltaic module according to claim 1, characterized in that: The step of obtaining the available area of ​​the tiled photovoltaic modules according to the total area and the shadow area of ​​the distributed photovoltaic roof, and obtaining the theoretical laying quantity of the large-area tiled photovoltaic modules in combination with the specifications of the tiled photovoltaic modules, specifically includes: The available area of ​​the tiled photovoltaic module is obtained by subtracting the shadow area from the total area; Calculate the optimal inclination angle and optimal spacing of the tiled photovoltaic modules installed on the distributed photovoltaic roof according to the specifications and available area of ​​the tiled photovoltaic modules; The theoretical number of large-area tiled photovoltaic modules to be laid is calculated based on the available area, optimal tilt angle and optimal spacing.

7. A splitting system for large-area flat photovoltaic modules, characterized in that: include: A data acquisition module, used to collect orthophoto data and point cloud data of tiled photovoltaic modules; An image segmentation module, used to obtain vector information of the distributed photovoltaic roof according to the orthoimage data and the point cloud data, and obtain the total area of ​​the distributed photovoltaic roof according to the vector information; A light irradiation analysis module is used to extract the longitude and latitude information and the solar altitude angle of the distributed photovoltaic roof, and calculate the light irradiation direction according to the longitude and latitude information and the solar altitude angle; A shadow analysis module, used to obtain the shadow area of ​​the distributed photovoltaic roof according to the total area of ​​the distributed photovoltaic roof and the direction of light exposure; The theoretical laying quantity calculation module is used to obtain the available area of ​​the flat-laid photovoltaic modules according to the total area and shadow area of ​​the distributed photovoltaic roof, and to obtain the theoretical laying quantity of large-area flat-laid photovoltaic modules in combination with the specifications of the flat-laid photovoltaic modules to achieve segmentation.

8. A computer device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable in the processor, wherein the processor implements the steps of the method for dividing a large-area tiled photovoltaic module as claimed in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for dividing a large-area tiled photovoltaic module according to any one of claims 1 to 6 are implemented.

10. A computer program product, the computer product comprising a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for dividing a large-area tiled photovoltaic module according to any one of claims 1 to 6 are implemented.

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