Photovoltaic panel illegal capacity expansion identification method and system based on unmanned aerial vehicle, and medium

Abstract

The invention discloses a photovoltaic panel illegal capacity expansion identification method and system based on an unmanned aerial vehicle, and a medium, mainly relates to the technical field of photovoltaic panel illegal capacity expansion identification, and is used for solving the problem of relatively high misjudgment or missed judgment rate of an existing unified illegal capacity expansion identification scheme. Comprising the steps that the relation between the photovoltaic power generation amount of a photovoltaic panel and a corresponding power generation range is obtained, and when the photovoltaic power generation amount exceeds the power generation range, the unmanned aerial vehicle collects actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel; when the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data acquired last time, determining that a photovoltaic panel illegal capacity expansion phenomenon exists; and when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data acquired last time, updating the power generation range according to the current actual photovoltaic panel data, and when the photovoltaic power generation capacity exceeds the updated power generation range, determining that the photovoltaic panel illegal capacity expansion phenomenon exists.

Description

Technical Field

[0001] The present application relates to the technical field of identifying illegal expansion of photovoltaic panels, and in particular to a method, system and medium for identifying illegal expansion of photovoltaic panels based on drones. Background Art

[0002] In recent years, with the development of drone inspection technology, drones have been widely used in daily maintenance and troubleshooting of photovoltaic power stations due to their high-precision positioning, stable flight and efficient data collection capabilities.

[0003] The existing drone inspection scheme for photovoltaic panel violations is mainly as follows: formulate an inspection plan based on the layout and inspection needs of the photovoltaic power station. Determine the inspection area, inspection time and inspection frequency, etc. According to the inspection plan, equip the drone with good camera equipment to carry out the inspection task. Automatically fly through the preset route to shoot and inspect the photovoltaic power station. The drone will capture a large amount of images and infrared thermal imaging data. This data will be transmitted to the data analysis system, and the images will be deeply analyzed through professional algorithms and models to identify abnormal conditions of photovoltaic panels, such as illegal expansion.

[0004] However, due to differences in photovoltaic panel materials, structures, manufacturing processes, etc., different types of photovoltaic panels may show different characteristics in images and infrared thermal imaging. The unified processing and analysis method has a high rate of misjudgment or missed judgment. Summary of the invention

[0005] In view of the above-mentioned deficiencies in the prior art, the present application provides a method, system and medium for identifying illegal capacity expansion of photovoltaic panels based on drones, so as to solve the problem of high misjudgment or missed judgment rate of the existing unified illegal capacity expansion identification scheme.

[0006] In a first aspect, the present application provides a method for identifying illegal expansion of photovoltaic panels based on a drone, the method comprising: Based on historical data, a multi-dimensional photovoltaic panel database is built; wherein the multi-dimensional photovoltaic panel database includes a number of photovoltaic panel data, and the photovoltaic panel data at least includes: the corresponding relationship between the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, the tilt angle of the photovoltaic panel, and the photovoltaic power generation; the actual photovoltaic panel data of the photovoltaic panel is collected by drone; wherein the actual photovoltaic panel data at least includes: the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, and the tilt angle of the photovoltaic panel; based on the multi-dimensional photovoltaic panel database and the actual photovoltaic panel data According to the data, the power generation range of the current photovoltaic panel photovoltaic power generation is determined; the relationship between the photovoltaic panel photovoltaic power generation and the corresponding power generation range is obtained. When the photovoltaic power generation exceeds the power generation range, the drone collects the actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel; when the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data collected last time, it is determined that there is an illegal expansion of the photovoltaic panel; when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data collected last time, the power generation range is updated according to the current actual photovoltaic panel data. When the photovoltaic power generation exceeds the updated power generation range, it is determined that there is an illegal expansion of the photovoltaic panel.

[0007] The method for identifying illegal expansion of photovoltaic panels provided in the embodiment of the present application, because the multi-dimensional photovoltaic panel database covers various information of photovoltaic panels, such as manufacturer, structure, size, capacity, etc., this enables the system to adapt to photovoltaic panels of different types and specifications. At the same time, by updating the power generation range, the system can cope with changes in the state of photovoltaic panels and maintain the accuracy of identification. By building a multi-dimensional photovoltaic panel database and combining the actual photovoltaic panel data collected by drones, this method can more accurately determine the power generation range of photovoltaic panels, thereby effectively reducing the misjudgment or missed judgment rate. It helps to more accurately identify the illegal expansion of photovoltaic panels and improve the safety and stability of the power grid.

[0008] In one implementation of the present application, actual photovoltaic panel data of the photovoltaic panel is collected by using a drone, specifically including: The longitude and latitude of each photovoltaic panel are collected through the positioning device installed on the drone; the manufacturer, structure, size and capacity of the photovoltaic panels marked on the photovoltaic panels are collected through the image collector installed on the drone; the three-dimensional modeling data of the photovoltaic panels are collected by circling the drone; after the orthophotos of the photovoltaic panels are collected, GIS modeling software is used for post-processing to extract the illumination angle and tilt angle of the photovoltaic panels.

[0009] In one implementation of the present application, after collecting the orthophoto of the photovoltaic panel, post-processing is performed using GIS modeling software to extract the illumination angle and tilt angle of the photovoltaic panel, specifically including: The drone obtains the edge computing server corresponding to the current area; sends the collected orthophoto of the photovoltaic panel to the edge computing server; extracts the illumination angle and tilt angle of the photovoltaic panel through the GIS modeling software preset in the edge computing server; and returns the illumination angle and tilt angle to the drone.

[0010] In one implementation of the present application, based on the multi-dimensional photovoltaic panel database and the actual photovoltaic panel data, the power generation range of the current photovoltaic panel photovoltaic power generation is determined, specifically including: A number of photovoltaic panel data whose similarity with actual photovoltaic panel data exceeds a preset threshold are obtained from a multi-dimensional photovoltaic panel database, and then the maximum photovoltaic power generation and the minimum photovoltaic power generation are obtained therefrom; and the power generation range of the current photovoltaic panel photovoltaic power generation is determined to be: [minimum photovoltaic power generation, maximum photovoltaic power generation].

[0011] In one implementation of the present application, a plurality of photovoltaic panel data having a similarity with actual photovoltaic panel data exceeding a preset threshold is obtained from a multi-dimensional photovoltaic panel database, specifically including: using the formula: , calculate the similarity between the photovoltaic panel data in the current multi-dimensional photovoltaic panel database and the actual photovoltaic panel data; in, Represents the specific value of the i-th number of actual photovoltaic panel data; represents the specific value of the i-th number in the photovoltaic panel data; n represents the specific number of data in the actual photovoltaic panel data.

[0012] In the second aspect, the present application provides a photovoltaic panel illegal expansion identification system based on a drone, the system comprising: A building module is used to build a multi-dimensional photovoltaic panel database based on historical data; wherein the multi-dimensional photovoltaic panel database includes a number of photovoltaic panel data, and the photovoltaic panel data at least includes: the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, the tilt angle of the photovoltaic panel, and the correspondence between the photovoltaic power generation; a drone is used to collect actual photovoltaic panel data of the photovoltaic panel; wherein the actual photovoltaic panel data at least includes: the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, and the tilt angle of the photovoltaic panel; a determination module is used to, based on the multi-dimensional photovoltaic panel database and the actual photovoltaic panel data, Determine the power generation range of the current photovoltaic panel photovoltaic power generation; the secondary collection module is used to obtain the relationship between the photovoltaic panel photovoltaic power generation and the corresponding power generation range. When the photovoltaic power generation exceeds the power generation range, the drone collects the actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel; the expansion detection module is used to determine whether there is an illegal expansion of the photovoltaic panel when the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data collected last time; when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data collected last time, the power generation range is updated according to the current actual photovoltaic panel data. When the photovoltaic power generation exceeds the updated power generation range, it is determined that there is an illegal expansion of the photovoltaic panel.

[0013] In one implementation of the present application, the drone includes a positioning device, an image collector, and a circling flight collection unit. The positioning device is used to collect the longitude and latitude of each photovoltaic panel; the image collector is used to collect the manufacturer, structure, size, and capacity of the photovoltaic panels marked on the photovoltaic panels; the circling flight collection unit is used to collect three-dimensional modeling data of the photovoltaic panels by circling flight of the drone; after the orthophoto of the photovoltaic panel is collected, GIS modeling software is used for post-processing to extract the illumination angle and tilt angle of the photovoltaic panel.

[0014] In one implementation of the present application, the determination module includes a determination unit, which is used to obtain a number of photovoltaic panel data whose similarity with the actual photovoltaic panel data exceeds a preset threshold from a multi-dimensional photovoltaic panel database, and then obtain the maximum photovoltaic power generation and the minimum photovoltaic power generation therefrom; determine that the power generation range of the current photovoltaic panel photovoltaic power generation is: [minimum photovoltaic power generation, maximum photovoltaic power generation].

[0015] In one implementation of the present application, the determination unit includes a similarity calculation unit, which is used to calculate the similarity by the formula: , calculate the similarity between the photovoltaic panel data in the current multi-dimensional photovoltaic panel database and the actual photovoltaic panel data; where, Represents the specific value of the i-th number of actual photovoltaic panel data; represents the specific value of the i-th number in the photovoltaic panel data; n represents the specific number of data in the actual photovoltaic panel data.

[0016] In a third aspect, the present application provides a non-volatile computer storage medium having computer instructions stored thereon, which, when executed, implement a method for identifying illegal expansion of photovoltaic panels based on a drone, such as any of the above items.

[0017] Those skilled in the art can understand that the present application has at least the following beneficial effects: This application proposes a method, system and medium for identifying illegal expansion of photovoltaic panels based on drones. Since the multi-dimensional photovoltaic panel database covers various information of photovoltaic panels, such as manufacturer, structure, size, capacity, etc., this enables the system to adapt to photovoltaic panels of different types and specifications. At the same time, by updating the power generation range, the system can respond to changes in the state of photovoltaic panels and maintain the accuracy of identification. By building a multi-dimensional photovoltaic panel database and combining the actual photovoltaic panel data collected by drones, this method can more accurately determine the power generation range of photovoltaic panels, thereby effectively reducing the misjudgment or missed judgment rate. It helps to more accurately identify the illegal expansion of photovoltaic panels and improve the safety and stability of the power grid. It solves the problem of high misjudgment or missed judgment rate of the existing unified illegal expansion identification scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Some embodiments of the present disclosure are described below with reference to the accompanying drawings, in which: Figure 1 This is a flow chart of a method for identifying illegal expansion of photovoltaic panels based on drones provided in an embodiment of the present application.

[0019] Figure 2 It is a schematic diagram of the internal structure of a photovoltaic panel illegal expansion identification system based on a drone provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] It should be understood by those skilled in the art that the embodiments described below are only preferred embodiments of the present disclosure, and do not mean that the present disclosure can only be implemented through the preferred embodiments. The preferred embodiments are only used to explain the technical principles of the present disclosure, and are not used to limit the protection scope of the present disclosure. Based on the preferred embodiments provided by the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work should still fall within the protection scope of the present disclosure.

[0021] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0022] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0023] The embodiment provides a method for identifying illegal expansion of photovoltaic panels based on drones, such as Figure 1 As shown, the method provided in the embodiment of the present application mainly includes the following steps: Step 110: Build a multi-dimensional photovoltaic panel database based on historical data.

[0024] It should be noted that the multidimensional photovoltaic panel database includes a number of photovoltaic panel data, and the photovoltaic panel data at least includes: the correspondence between the photovoltaic panel manufacturer, photovoltaic panel structure, photovoltaic panel size, photovoltaic panel capacity, photovoltaic panel longitude and latitude, lighting angle, photovoltaic panel tilt angle, and photovoltaic power generation.

[0025] In addition, the construction process can be specifically to select a recent period of time in the total database, for example, the photovoltaic power generation set of photovoltaic panels that have not been illegally expanded in the past year. Combined with the manufacturer, structure, size, capacity, longitude and latitude of photovoltaic panels, illumination angle, and tilt angle of photovoltaic panels collected at several times in the past year, photovoltaic panel data is constructed. Each collection here will simultaneously collect the manufacturer, structure, size, capacity, longitude and latitude of photovoltaic panels, illumination angle, and tilt angle of photovoltaic panels. In addition, the means of collection can be manual collection or collection using drones.

[0026] Step 120: Collect actual photovoltaic panel data of the photovoltaic panel through the drone.

[0027] It should be noted that the actual photovoltaic panel data includes at least: the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the lighting angle, and the tilt angle of the photovoltaic panel.

[0028] In addition, this step can be specifically as follows: The longitude and latitude of each photovoltaic panel are collected through the positioning device installed on the drone; the manufacturer, structure, size and capacity of the photovoltaic panels marked on the photovoltaic panels are collected through the image collector installed on the drone; the photovoltaic panels are used to collect three-dimensional modeling data by circling the drone; after the orthophotos of the photovoltaic panels are collected, GIS (Geographic Information System) modeling software is used for post-processing to extract the illumination angle and tilt angle of the photovoltaic panels.

[0029] Here, after collecting the orthophoto of the photovoltaic panel, GIS modeling software is used for post-processing to extract the illumination angle and tilt angle of the photovoltaic panel, which can be specifically: The drone obtains the edge computing server corresponding to the current area; sends the collected orthophoto of the photovoltaic panel to the edge computing server; extracts the illumination angle and tilt angle of the photovoltaic panel through the GIS modeling software preset in the edge computing server; and returns the illumination angle and tilt angle to the drone.

[0030] It should be noted that, after determining the flight area of ​​the drone, those skilled in the art can establish a communication relationship between the drone and the edge computing server in the corresponding area.

[0031] Step 130: Determine the power generation range of the current photovoltaic panel photovoltaic power generation based on the multi-dimensional photovoltaic panel database and actual photovoltaic panel data.

[0032] In some implementations, this step may be specifically as follows: obtaining from a multidimensional photovoltaic panel database a number of photovoltaic panel data whose similarity with actual photovoltaic panel data exceeds a preset threshold, and then obtaining therefrom a maximum photovoltaic power generation and a minimum photovoltaic power generation; determining that the power generation range of the current photovoltaic panel photovoltaic power generation is: [minimum photovoltaic power generation, maximum photovoltaic power generation].

[0033] Here, a number of photovoltaic panel data whose similarity with the actual photovoltaic panel data exceeds a preset threshold are obtained from the multi-dimensional photovoltaic panel database, which can be specifically: By formula: , calculate the similarity between the photovoltaic panel data in the current multi-dimensional photovoltaic panel database and the actual photovoltaic panel data; where, Represents the specific value of the i-th number of actual photovoltaic panel data; represents the specific value of the i-th number in the photovoltaic panel data; n represents the specific number of data in the actual photovoltaic panel data.

[0034] Step 140, obtaining the relationship between the photovoltaic power generation of the photovoltaic panel and the corresponding power generation range. When the photovoltaic power generation exceeds the power generation range, the drone collects the actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel.

[0035] It should be noted that by clarifying the relationship between photovoltaic power generation and the corresponding power generation range, the power generation of photovoltaic power stations can be estimated more accurately, providing a reliable basis for power station planning and operation. In addition, in order to avoid the frequent use of drones causing a large amount of data stacking, this application accurately collects data from some photovoltaic panels according to the longitude and latitude of the photovoltaic panels when the photovoltaic power generation exceeds the power generation range, reducing the resource loss caused by data stacking and processing the number of stacks.

[0036] Step 150: When the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data collected last time, it is determined that there is an illegal expansion of the photovoltaic panel capacity; when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data collected last time, the power generation range is updated according to the current actual photovoltaic panel data, and when the photovoltaic power generation exceeds the updated power generation range, it is determined that there is an illegal expansion of the photovoltaic panel capacity.

[0037] It should be noted that by comparing the current and last collected photovoltaic panel data, it is possible to accurately determine whether the photovoltaic panel has been illegally expanded. If the data is consistent but the power generation exceeds expectations, it is likely that there is unauthorized expansion, which helps to promptly detect and deal with violations. In addition, since some external factors may affect the value of photovoltaic power generation, this application updates the power generation range based on the current actual photovoltaic panel data, which helps to more accurately reduce the occurrence of misjudgments.

[0038] In addition, this application Figure 2 The present application provides a photovoltaic panel illegal expansion identification system based on drones. Figure 2 As shown, the system provided in the embodiment of the present application mainly includes: Building module 210 is used to build a multi-dimensional photovoltaic panel database based on historical data; wherein the multi-dimensional photovoltaic panel database includes a number of photovoltaic panel data, and the photovoltaic panel data at least includes: the correspondence between the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, the tilt angle of the photovoltaic panel, and the photovoltaic power generation.

[0039] The drone 220 is used to collect actual photovoltaic panel data of the photovoltaic panel; wherein the actual photovoltaic panel data at least includes: the manufacturer of the photovoltaic panel, the photovoltaic panel structure, the photovoltaic panel size, the photovoltaic panel capacity, the photovoltaic panel longitude and latitude, the illumination angle, and the photovoltaic panel tilt angle.

[0040] The drone 220 includes a positioning device, an image collector, and a circling flight collection unit. The positioning device is used to collect the longitude and latitude of each photovoltaic panel; the image collector is used to collect the manufacturer, structure, size, and capacity of the photovoltaic panels marked on the photovoltaic panels; the circling flight collection unit is used to collect three-dimensional modeling data of the photovoltaic panels by circling flight of the drone; after collecting the orthophoto of the photovoltaic panel, GIS modeling software is used for post-processing to extract the illumination angle and tilt angle of the photovoltaic panel.

[0041] The determination module 230 is used to determine the power generation range of the current photovoltaic panel photovoltaic power generation based on the multi-dimensional photovoltaic panel database and the actual photovoltaic panel data.

[0042] The determination module 230 includes a determination unit, which is used to obtain a number of photovoltaic panel data whose similarity with the actual photovoltaic panel data exceeds a preset threshold from the multi-dimensional photovoltaic panel database, and then obtain the maximum photovoltaic power generation and the minimum photovoltaic power generation therefrom; determine that the power generation range of the current photovoltaic panel photovoltaic power generation is: [minimum photovoltaic power generation, maximum photovoltaic power generation].

[0043] The determination unit includes a similarity calculation unit for calculating the similarity by the formula: , calculate the similarity between the photovoltaic panel data in the current multi-dimensional photovoltaic panel database and the actual photovoltaic panel data; where, Represents the specific value of the i-th number of actual photovoltaic panel data; represents the specific value of the i-th number in the photovoltaic panel data; n represents the specific number of data in the actual photovoltaic panel data.

[0044] The secondary collection module 240 is used to obtain the relationship between the photovoltaic power generation of the photovoltaic panel and the corresponding power generation range. When the photovoltaic power generation exceeds the power generation range, the drone 220 collects the actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel; The expansion detection module 250 is used to determine that there is an illegal expansion of the photovoltaic panel when the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data collected last time; when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data collected last time, update the power generation range according to the current actual photovoltaic panel data, and when the photovoltaic power generation exceeds the updated power generation range, it is determined that there is an illegal expansion of the photovoltaic panel.

[0045] In addition, an embodiment of the present application further provides a non-volatile computer storage medium on which executable instructions are stored. When the executable instructions are executed, a method for identifying illegal expansion of photovoltaic panels based on a drone as described above is implemented.

[0046] So far, the technical solutions of the present disclosure have been described in combination with the above multiple embodiments, but it is easy for those skilled in the art to understand that the protection scope of the present disclosure is not limited to these specific embodiments. Without departing from the technical principles of the present disclosure, those skilled in the art can split and combine the technical solutions in the above-mentioned various embodiments, and can also make equivalent changes or replacements to the relevant technical features. Any changes, equivalent replacements, improvements, etc. made within the technical concept and / or technical principle of the present disclosure will fall within the protection scope of the present disclosure.

Claims

1. A method for identifying illegal expansion of photovoltaic panels based on drones, characterized in that: The method comprises: Based on historical data, a multi-dimensional photovoltaic panel database is built; wherein the multi-dimensional photovoltaic panel database includes a number of photovoltaic panel data, and the photovoltaic panel data at least includes: the corresponding relationship between the photovoltaic panel manufacturer, photovoltaic panel structure, photovoltaic panel size, photovoltaic panel capacity, photovoltaic panel longitude and latitude, illumination angle, photovoltaic panel tilt angle, and photovoltaic power generation; The actual photovoltaic panel data of the photovoltaic panel is collected by drones; wherein the actual photovoltaic panel data at least includes: the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, and the tilt angle of the photovoltaic panel; Based on the multi-dimensional photovoltaic panel database and actual photovoltaic panel data, determine the power generation range of the current photovoltaic panel photovoltaic power generation; Obtain the relationship between the photovoltaic power generation of the photovoltaic panel and the corresponding power generation range. When the photovoltaic power generation exceeds the power generation range, the drone collects the actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel; When the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data collected last time, it is determined that there is an illegal expansion of the photovoltaic panel capacity; when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data collected last time, the power generation range is updated according to the current actual photovoltaic panel data. When the photovoltaic power generation exceeds the updated power generation range, it is determined that there is an illegal expansion of the photovoltaic panel capacity.

2. The method for identifying illegal expansion of photovoltaic panels based on drones according to claim 1 is characterized in that: The actual photovoltaic panel data of the photovoltaic panels are collected by drones, including: The latitude and longitude of each photovoltaic panel are collected through the positioning device set on the drone; The image collector installed on the drone collects the manufacturer, structure, size and capacity of the photovoltaic panels marked on the photovoltaic panels; Use drones to fly around and collect data for 3D modeling of photovoltaic panels. After collecting orthophotos of the photovoltaic panels, use GIS modeling software for post-processing to extract the illumination angle and tilt angle of the photovoltaic panels.

3. The method for identifying illegal expansion of photovoltaic panels based on drones according to claim 2 is characterized in that: After collecting the orthophotos of the photovoltaic panels, post-processing is performed using GIS modeling software to extract the illumination angle and tilt angle of the photovoltaic panels, including: The drone obtains the edge computing server corresponding to the current area; Send the collected orthophotos of photovoltaic panels to the edge computing server; The illumination angle and tilt angle of the photovoltaic panel are extracted through the GIS modeling software preset in the edge computing server; Returns the light angle and tilt angle to the drone.

4. The method for identifying illegal expansion of photovoltaic panels based on drones according to claim 1 is characterized in that: Based on the multi-dimensional photovoltaic panel database and actual photovoltaic panel data, the power generation range of the current photovoltaic panel photovoltaic power generation is determined, including: A number of photovoltaic panel data whose similarity with actual photovoltaic panel data exceeds a preset threshold are obtained from a multi-dimensional photovoltaic panel database, and then the maximum photovoltaic power generation and the minimum photovoltaic power generation are obtained therefrom; and the power generation range of the current photovoltaic panel photovoltaic power generation is determined to be: [minimum photovoltaic power generation, maximum photovoltaic power generation].

5. The method for identifying illegal expansion of photovoltaic panels based on drones according to claim 4 is characterized in that: A number of photovoltaic panel data with similarities exceeding a preset threshold with actual photovoltaic panel data are obtained from the multi-dimensional photovoltaic panel database, specifically including: By formula: , calculate the similarity between the photovoltaic panel data in the current multi-dimensional photovoltaic panel database and the actual photovoltaic panel data; in, Represents the specific value of the i-th number of actual photovoltaic panel data; represents the specific value of the i-th number in the photovoltaic panel data; n represents the specific number of data in the actual photovoltaic panel data.

6. A photovoltaic panel illegal expansion identification system based on drones, characterized in that: The system comprises: A building module is used to build a multi-dimensional photovoltaic panel database based on historical data; wherein the multi-dimensional photovoltaic panel database includes a number of photovoltaic panel data, and the photovoltaic panel data at least includes: the corresponding relationship between the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, the tilt angle of the photovoltaic panel, and the photovoltaic power generation; The drone is used to collect actual photovoltaic panel data of the photovoltaic panel; wherein the actual photovoltaic panel data at least includes: the manufacturer of the photovoltaic panel, the structure of the photovoltaic panel, the size of the photovoltaic panel, the capacity of the photovoltaic panel, the longitude and latitude of the photovoltaic panel, the illumination angle, and the tilt angle of the photovoltaic panel; A determination module, for determining a power generation range of a current photovoltaic panel photovoltaic power generation based on a multi-dimensional photovoltaic panel database and actual photovoltaic panel data; The secondary collection module is used to obtain the relationship between the photovoltaic power generation of the photovoltaic panel and the corresponding power generation range. When the photovoltaic power generation exceeds the power generation range, the drone collects the actual photovoltaic panel data of the photovoltaic panel again according to the longitude and latitude of the photovoltaic panel; The expansion detection module is used to determine that there is an illegal expansion of the photovoltaic panel when the current actual photovoltaic panel data is consistent with the actual photovoltaic panel data collected last time; when the current actual photovoltaic panel data is inconsistent with the actual photovoltaic panel data collected last time, the power generation range is updated according to the current actual photovoltaic panel data. When the photovoltaic power generation exceeds the updated power generation range, it is determined that there is an illegal expansion of the photovoltaic panel.

7. The photovoltaic panel illegal expansion identification system based on drone according to claim 6 is characterized in that: The UAV includes a positioning device, an image collector, and a circling flight acquisition unit. A positioning device for collecting the longitude and latitude of each photovoltaic panel; An image collector is used to collect information on the photovoltaic panels, including the manufacturer, structure, size and capacity of the photovoltaic panels; The orbiting flight acquisition unit is used to collect data for three-dimensional modeling of photovoltaic panels by using an UAV to orbit. After collecting the orthophoto of the photovoltaic panel, GIS modeling software is used for post-processing to extract the illumination angle and tilt angle of the photovoltaic panel.

8. The photovoltaic panel illegal expansion identification system based on drone according to claim 6 is characterized in that: The determination module comprises a determination unit, It is used to obtain a number of photovoltaic panel data whose similarity with the actual photovoltaic panel data exceeds a preset threshold from the multi-dimensional photovoltaic panel database, and then obtain the maximum photovoltaic power generation and the minimum photovoltaic power generation from them; determine that the power generation range of the current photovoltaic panel photovoltaic power generation is: [minimum photovoltaic power generation, maximum photovoltaic power generation].

9. The photovoltaic panel illegal expansion identification system based on drone according to claim 8 is characterized in that: The determination unit includes a similarity calculation unit, Used by the formula: , calculate the similarity between the photovoltaic panel data in the current multi-dimensional photovoltaic panel database and the actual photovoltaic panel data; in, Represents the specific value of the i-th number of actual photovoltaic panel data; represents the specific value of the i-th number in the photovoltaic panel data; n represents the specific number of data in the actual photovoltaic panel data.

10. A non-volatile computer storage medium, characterized in that: Computer instructions are stored thereon, and when the computer instructions are executed, a method for identifying illegal expansion of photovoltaic panels based on a drone is implemented as described in any one of claims 1 to 5.

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