A method and device for identifying data anomalies in a photovoltaic plant

Abstract

The present invention relates to the field of electric power operation and maintenance technology, and in particular to a method for identifying data anomalies in a photovoltaic plant. An embodiment of the present invention provides a method for identifying data anomalies in a photovoltaic plant, comprising: obtaining the infrared radiation intensity of each photovoltaic panel collected by an infrared camera above the photovoltaic plant; obtaining the distance of each photovoltaic panel from the depth camera collected by a depth camera above the photovoltaic plant; calculating the temperature of each photovoltaic panel based on the infrared radiation intensity and the distance of each photovoltaic panel; and judging whether there is an anomaly in the photovoltaic panel based on the power generation, temperature, and light intensity of each photovoltaic panel. An embodiment of the present invention provides a method for identifying data anomalies in a photovoltaic plant, which can accurately locate the problem photovoltaic panel through data anomalies, so that staff can conduct rapid and targeted maintenance.

Description

Technical Field

[0001] The present invention relates to the field of power operation and maintenance technology, and in particular to a method and device for identifying data anomalies in a photovoltaic plant. Background Art

[0002] Photovoltaic plants are often located in the northwest, making them unsuitable for long-term staff presence. However, the status of the photovoltaic panels used in these plants' power generation equipment needs to be monitored, allowing for prompt repairs if any issues arise. Regularly inspecting and servicing a large number of panels requires significant time and effort from specialized personnel. Therefore, a data anomaly identification method for photovoltaic plants is urgently needed to accurately pinpoint problematic panels based on data anomalies, enabling rapid and targeted repairs. Summary of the Invention

[0003] The embodiments of the present invention provide a data anomaly identification method, device, electronic device and storage medium for a photovoltaic plant, which can accurately locate problematic photovoltaic panels through data anomalies, allowing staff to perform rapid and targeted maintenance.

[0004] In a first aspect, an embodiment of the present invention provides a method for identifying data anomalies in a photovoltaic plant, comprising:

[0005] Obtain the infrared radiation intensity of each photovoltaic panel using an infrared camera above the photovoltaic plant;

[0006] Obtaining the distance between each photovoltaic panel and the depth camera collected by the depth camera above the photovoltaic plant;

[0007] Calculating the temperature of each photovoltaic panel based on the infrared radiation intensity of each photovoltaic panel and the distance;

[0008] Determine whether there is any abnormality in each photovoltaic panel based on its power generation, temperature and light intensity.

[0009] In one possible design, calculating the temperature of each photovoltaic panel based on the infrared radiation intensity and the distance of each photovoltaic panel includes:

[0010] Establishing an infrared radiation matrix according to the infrared radiation intensity of each photovoltaic panel collected by the infrared camera;

[0011] Establishing a distance matrix according to the distance of each photovoltaic panel collected by the depth camera;

[0012] Determining a coordinate transformation matrix between the infrared camera and the depth camera according to a positional relationship between the infrared camera, the depth camera, and a ground plane;

[0013] A temperature matrix including the temperature of each photovoltaic panel is determined according to the infrared radiation matrix, the distance matrix, and the coordinate transformation matrix.

[0014] In one possible design, determining whether there is an abnormality in each photovoltaic panel based on the power generation, temperature, and light intensity of the photovoltaic panel includes:

[0015] Establish a detection model based on the normal light intensity, temperature and power generation of photovoltaic panels;

[0016] Relying on the detection model, it is determined whether there is any abnormality in the photovoltaic panel based on the collected light intensity matrix, temperature matrix and power generation matrix; wherein the power generation matrix includes the power generation of each photovoltaic panel, and the light intensity matrix includes the light intensity of each photovoltaic panel.

[0017] In one possible design, solar radiation values, solar altitude angles, PM values, and the inclination angle of each photovoltaic panel are collected to calculate the light intensity received by each photovoltaic panel.

[0018] In one possible design, it also includes:

[0019] Using an RGB camera above the photovoltaic plant, the image color of each photovoltaic panel is captured;

[0020] The image color of each photovoltaic panel captured by the RGB camera;

[0021] Using the test data, the degree to which the intensity of light received by the photovoltaic panels is weakened by dust of different thicknesses on the photovoltaic panels is fitted;

[0022] determining the thickness of dust on each photovoltaic panel according to the color of the image on each photovoltaic panel;

[0023] determining, based on the thickness of the dust on the photovoltaic panel, the extent to which the dust weakens the light intensity received by the photovoltaic panel;

[0024] The light intensity matrix is ​​determined according to the light intensity and the weakening degree of each photovoltaic panel.

[0025] In a possible design, it also includes: when the image color is not within a preset color range, arranging a cleaning robot to clean the corresponding photovoltaic panel.

[0026] In one possible design, the test data includes experimental data and / or simulation data.

[0027] In a second aspect, an embodiment of the present invention further provides a data anomaly identification device for a photovoltaic plant, comprising:

[0028] The first unit is used to obtain the infrared radiation intensity of each photovoltaic panel collected by an infrared camera above the photovoltaic plant;

[0029] The second unit is used to obtain the distance between each photovoltaic panel and the depth camera collected by the depth camera above the photovoltaic plant;

[0030] a third unit, configured to calculate the temperature of each photovoltaic panel according to the infrared radiation intensity of each photovoltaic panel and the distance;

[0031] The fourth unit is used to determine whether there is any abnormality in each photovoltaic panel based on the power generation, temperature and light intensity of each photovoltaic panel.

[0032] In a third aspect, an embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in any embodiment of this specification is implemented.

[0033] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, enables the computer to execute the method described in any embodiment of this specification.

[0034] Compared with the prior art, the present invention has at least the following beneficial effects:

[0035] In this embodiment, the temperature of each photovoltaic panel can be initially obtained by collecting the infrared radiation intensity of each photovoltaic panel. However, in order to collect data from all photovoltaic panels, the infrared camera needs to be at a certain height and distance so that all photovoltaic panels are within the infrared camera's field of view. Therefore, there is a certain distance between the photovoltaic panel and the infrared camera, and the distance between each photovoltaic panel and the infrared camera is different. Therefore, in order to obtain more accurate temperature data, it is necessary to use a depth camera to measure the distance between each photovoltaic panel and the depth camera. Based on the conversion coordinate system between the depth camera and the infrared camera, the distance between the infrared camera and the photovoltaic panel can be obtained based on the distance between the depth camera and the photovoltaic panel. The infrared radiation intensity is then calibrated based on the distance between the infrared camera and the photovoltaic panel to obtain an accurate temperature. After obtaining the temperature data, the temperature data is combined with the light intensity and power generation to determine whether there are any anomalies in the data, thereby accurately locating the corresponding photovoltaic panel. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0037] Figure 1This is a flow chart of a method for identifying data anomalies in a photovoltaic plant area provided by one embodiment of the present invention;

[0038] Figure 2 This is a hardware architecture diagram of an electronic device provided by one embodiment of the present invention;

[0039] Figure 3 This is a structural diagram of a data anomaly identification device for a photovoltaic plant provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] The specific implementation of the above concept is described below.

[0042] Please refer to Figure 1 , an embodiment of the present invention provides a method for identifying data anomalies in a photovoltaic plant, the method comprising:

[0043] Obtain the infrared radiation intensity of each photovoltaic panel using an infrared camera above the photovoltaic plant;

[0044] Obtaining the distance between each photovoltaic panel and the depth camera collected by the depth camera above the photovoltaic plant;

[0045] Calculate the temperature of each photovoltaic panel based on the infrared radiation intensity and distance of each photovoltaic panel;

[0046] Determine whether there is any abnormality in each photovoltaic panel based on its power generation, temperature and light intensity.

[0047] In this embodiment, the temperature of each photovoltaic panel can be initially obtained by collecting the infrared radiation intensity of each photovoltaic panel. However, in order to collect data from all photovoltaic panels, the infrared camera needs to be at a certain height and distance so that all photovoltaic panels are within the infrared camera's field of view. Therefore, there is a certain distance between the photovoltaic panel and the infrared camera, and the distance between each photovoltaic panel and the infrared camera is different. Therefore, in order to obtain more accurate temperature data, it is necessary to use a depth camera to measure the distance between each photovoltaic panel and the depth camera. Based on the conversion coordinate system between the depth camera and the infrared camera, the distance between the infrared camera and the photovoltaic panel can be obtained based on the distance between the depth camera and the photovoltaic panel. The infrared radiation intensity is then calibrated based on the distance between the infrared camera and the photovoltaic panel to obtain an accurate temperature. After obtaining the temperature data, the temperature data is combined with the light intensity and power generation to determine whether there are any anomalies in the data, thereby accurately locating the corresponding photovoltaic panel.

[0048] It should be noted that when performing temperature calculations, water vapor and carbon dioxide data, which have a certain scattering effect on infrared radiation, can also be combined.

[0049] It's important to note that temperature affects photovoltaic panels in two ways. First, temperature itself affects their photovoltaic efficiency. Higher temperatures reduce this efficiency, and the lower the efficiency, the higher the proportion of light intensity used for heat generation, creating a vicious cycle. Recording the relationship between temperature, light intensity, and power generation can help detect photovoltaic panel anomalies and, based on historical data, predict the panel's status and usage. Second, the temperature of a photovoltaic panel also affects the status of other internal components, making collecting temperature data equally important.

[0050] In some embodiments of the present invention, calculating the temperature of each photovoltaic panel based on the infrared radiation intensity and distance of each photovoltaic panel includes:

[0051] An infrared radiation matrix is ​​established based on the infrared radiation intensity of each photovoltaic panel collected by the infrared camera;

[0052] Establish a distance matrix based on the distance of each photovoltaic panel collected by the depth camera;

[0053] Determine the coordinate transformation matrix between the infrared camera and the depth camera based on the positional relationship between the infrared camera, the depth camera, and the ground plane;

[0054] A temperature matrix including the temperature of each photovoltaic panel is determined according to the infrared radiation matrix, the distance matrix and the coordinate transformation matrix.

[0055] In some embodiments of the present invention, determining whether there is an abnormality in each photovoltaic panel based on the power generation, temperature, and light intensity of each photovoltaic panel includes:

[0056] Establish a detection model based on the normal light intensity, temperature and power generation of photovoltaic panels;

[0057] Relying on the detection model, whether there is any abnormality in the photovoltaic panel is determined based on the collected light intensity matrix, temperature matrix and power generation matrix; among them, the power generation matrix includes the power generation of each photovoltaic panel, and the light intensity matrix includes the light intensity of each photovoltaic panel.

[0058] In this embodiment, a detection model can be established based on deep learning. The detection model can predict the power generation based on temperature and light intensity. The power generation under normal conditions can be calculated by collecting temperature and light intensity. If there is a difference between the current power generation and the calculated power generation, it will be marked as abnormal data.

[0059] In some embodiments of the present invention, solar radiation values, solar altitude angles, PM values, and the inclination angle of each photovoltaic panel are collected to calculate the light intensity received by each photovoltaic panel.

[0060] In this embodiment, the solar altitude angle and the inclination angle of the photovoltaic panel can determine the incident angle, and combined with the solar radiation intensity and the PM value (particulate matter content in the air), the precise light intensity incident on the photovoltaic panel can be determined.

[0061] In some embodiments of the present invention, further comprising:

[0062] Using an RGB camera above the photovoltaic plant, the image color of each photovoltaic panel is captured;

[0063] According to the image color of each photovoltaic panel captured by the RGB camera;

[0064] Using the test data, the degree to which the intensity of light received by the photovoltaic panels is weakened by dust of different thicknesses on the photovoltaic panels is fitted;

[0065] Determine the dust thickness on each photovoltaic panel based on the image color on each photovoltaic panel;

[0066] Determine the degree to which the dust weakens the light intensity received by the photovoltaic panels based on the thickness of the dust on the photovoltaic panels;

[0067] The light intensity matrix is ​​determined based on the light intensity and the attenuation level of each photovoltaic panel.

[0068] In this embodiment, floating sand on the photovoltaic panels will weaken the light they receive, and the degree of weakening is related to the thickness of the sand. Therefore, an RGB camera can be used to capture the color image of the photovoltaic panels, and the thickness of the sand can be estimated based on the image color to correct the light intensity.

[0069] In some embodiments of the present invention, the method further includes: when the image color is not within a preset color range, arranging a cleaning robot to clean the corresponding photovoltaic panel.

[0070] In some embodiments of the present invention, the test data includes experimental data and / or simulation data.

[0071] like Figure 2 、 Figure 3 As shown, an embodiment of the present invention provides a data anomaly identification device for a photovoltaic plant. The device embodiment can be implemented by software, hardware, or a combination of software and hardware. From the hardware level, Figure 2 The figure shows a hardware architecture diagram of an electronic device where a data anomaly identification device for a photovoltaic plant is located according to an embodiment of the present invention. Figure 2 In addition to the processor, memory, network interface, and non-volatile memory shown, the electronic device in the embodiment may also include other hardware, such as a forwarding chip responsible for processing messages, etc. Taking software implementation as an example, Figure 3 As shown, as a device in a logical sense, the CPU of the electronic device in which it is located reads the corresponding computer program in the non-volatile memory into the internal memory and runs it. This embodiment provides a data anomaly identification device for a photovoltaic plant, including:

[0072] The first unit is used to obtain the infrared radiation intensity of each photovoltaic panel collected by an infrared camera above the photovoltaic plant;

[0073] The second unit is used to obtain the distance between each photovoltaic panel and the depth camera collected by the depth camera above the photovoltaic plant;

[0074] a third unit, configured to calculate the temperature of each photovoltaic panel according to the infrared radiation intensity of each photovoltaic panel and the distance;

[0075] The fourth unit is used to determine whether there is any abnormality in each photovoltaic panel based on the power generation, temperature and light intensity of each photovoltaic panel.

[0076] In some embodiments of the present invention, the third unit is further configured to perform the following operations:

[0077] An infrared radiation matrix is ​​established based on the infrared radiation intensity of each photovoltaic panel collected by the infrared camera;

[0078] Establish a distance matrix based on the distance of each photovoltaic panel collected by the depth camera;

[0079] Determine the coordinate transformation matrix between the infrared camera and the depth camera based on the positional relationship between the infrared camera, the depth camera, and the ground plane;

[0080] A temperature matrix including the temperature of each photovoltaic panel is determined according to the infrared radiation matrix, the distance matrix and the coordinate transformation matrix.

[0081] In some embodiments of the present invention, the fourth unit is configured to perform the following operations:

[0082] Establish a detection model based on the normal light intensity, temperature and power generation of photovoltaic panels;

[0083] Relying on the detection model, whether there is any abnormality in the photovoltaic panel is determined based on the collected light intensity matrix, temperature matrix and power generation matrix; among them, the power generation matrix includes the power generation of each photovoltaic panel, and the light intensity matrix includes the light intensity of each photovoltaic panel.

[0084] In some embodiments of the present invention, solar radiation values, solar altitude angles, PM values, and the inclination angle of each photovoltaic panel are collected to calculate the light intensity received by each photovoltaic panel.

[0085] In some embodiments of the present invention, a fifth unit is further included, and the fifth unit is configured to perform the following operations:

[0086] Using an RGB camera above the photovoltaic plant, the image color of each photovoltaic panel is captured;

[0087] According to the image color of each photovoltaic panel captured by the RGB camera;

[0088] Using the test data, the degree to which the intensity of light received by the photovoltaic panels is weakened by dust of different thicknesses on the photovoltaic panels is fitted;

[0089] Determine the dust thickness on each photovoltaic panel based on the image color on each photovoltaic panel;

[0090] Determine the degree to which the dust weakens the light intensity received by the photovoltaic panels based on the thickness of the dust on the photovoltaic panels;

[0091] The light intensity matrix is ​​determined based on the light intensity and the attenuation level of each photovoltaic panel.

[0092] In some embodiments of the present invention, a sixth unit is further included, and the sixth unit is used to execute: when the image color is not within the preset color range, arranging a cleaning robot to clean the corresponding photovoltaic panel.

[0093] In some embodiments of the present invention, the test data includes experimental data and / or simulation data.

[0094] It should be understood that the structure illustrated in the embodiments of the present invention does not constitute a specific limitation on a data anomaly identification device for a photovoltaic plant. In other embodiments of the present invention, a data anomaly identification device for a photovoltaic plant may include more or fewer components than illustrated, or may combine or separate certain components, or employ different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of both.

[0095] The information interaction, execution process, etc. between the modules in the above-mentioned device are based on the same concept as the embodiment of the method of the present invention. For specific contents, please refer to the description in the embodiment of the method of the present invention and will not be repeated here.

[0096] An embodiment of the present invention further provides an electronic device including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a data anomaly identification method for a photovoltaic plant area according to any embodiment of the present invention is implemented.

[0097] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor executes a data anomaly identification method for a photovoltaic plant area according to any embodiment of the present invention.

[0098] Specifically, a system or device equipped with a storage medium can be provided, on which software program codes that implement the functions of any of the above-mentioned embodiments are stored, and a computer (or CPU or MPU) of the system or device can be enabled to read and execute the program codes stored in the storage medium.

[0099] In this case, the program code itself read from the storage medium can realize the function of any one of the above-mentioned embodiments, and thus the program code and the storage medium storing the program code constitute part of the present invention.

[0100] Examples of storage media for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROMs, CD-Rs, CD-RWs, DVD-ROMs, DVD-RAMs, DVD-RWs, and DVD+RWs), magnetic tapes, non-volatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer via a communications network.

[0101] In addition, it should be clear that the functions of any of the above embodiments can be achieved not only by executing the program code read by the computer, but also by enabling the operating system operating on the computer to complete part or all of the actual operations based on the instructions of the program code.

[0102] In addition, it can be understood that the program code read from the storage medium is written into a memory provided in an expansion board inserted into the computer or into a memory provided in an expansion module connected to the computer, and then based on the instructions of the program code, a CPU installed on the expansion board or expansion module is enabled to perform part or all of the actual operations, thereby realizing the functions of any of the above embodiments.

[0103] It should be noted that, in this article, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises", "comprising" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising 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, article or device. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical factors in the process, method, article or device comprising the elements.

[0104] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk, etc. Various media that can store program codes.

[0105] 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 aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for identifying data anomalies in a photovoltaic plant, characterized in that: include: Obtain the infrared radiation intensity of each photovoltaic panel using an infrared camera above the photovoltaic plant; Obtaining the distance between each photovoltaic panel and the depth camera collected by the depth camera above the photovoltaic plant; Calculating the temperature of each photovoltaic panel based on the infrared radiation intensity and the distance of each photovoltaic panel; wherein, when calculating the temperature, water vapor and carbon dioxide data having a scattering effect on infrared radiation are combined; Determine whether there is any abnormality in each photovoltaic panel based on its power generation, temperature and light intensity; Calculating the temperature of each photovoltaic panel according to the infrared radiation intensity and the distance of each photovoltaic panel includes: Establishing an infrared radiation matrix according to the infrared radiation intensity of each photovoltaic panel collected by the infrared camera; Establishing a distance matrix according to the distance of each photovoltaic panel collected by the depth camera; Determining a coordinate transformation matrix between the infrared camera and the depth camera according to a positional relationship between the infrared camera, the depth camera, and a ground plane; determining a temperature matrix including the temperature of each photovoltaic panel according to the infrared radiation matrix, the distance matrix and the coordinate transformation matrix; The step of determining whether there is an abnormality in each photovoltaic panel based on the power generation, temperature, and light intensity of each photovoltaic panel includes: Establish a detection model based on the normal light intensity, temperature and power generation of photovoltaic panels; Relying on the detection model, it is determined whether there is any abnormality in the photovoltaic panel based on the collected light intensity matrix, temperature matrix and power generation matrix; wherein the power generation matrix includes the power generation of each photovoltaic panel, and the light intensity matrix includes the light intensity of each photovoltaic panel.

2. The method according to claim 1, characterized in that Collect solar radiation values, solar altitude angles, PM values, and the inclination angle of each photovoltaic panel to calculate the light intensity received by each photovoltaic panel.

3. The method according to claim 1, characterized in that Also includes: Using an RGB camera above the photovoltaic plant, the image color of each photovoltaic panel is captured; The image color of each photovoltaic panel captured by the RGB camera; Using the test data, the degree to which the intensity of light received by the photovoltaic panels is weakened by dust of different thicknesses on the photovoltaic panels is fitted; determining the thickness of dust on each photovoltaic panel according to the color of the image on each photovoltaic panel; determining, based on the thickness of the dust on the photovoltaic panel, the extent to which the dust weakens the light intensity received by the photovoltaic panel; The light intensity matrix is ​​determined according to the light intensity and the weakening degree of each photovoltaic panel.

4. The method according to claim 3, characterized in that Also includes: When the image color is not within the preset color range, the cleaning robot is arranged to clean the corresponding photovoltaic panel.

5. The method according to claim 3, characterized in that The test data includes experimental data and / or simulation data.

6. A data anomaly identification device for a photovoltaic plant, characterized in that: include: The first unit is used to obtain the infrared radiation intensity of each photovoltaic panel collected by an infrared camera above the photovoltaic plant; The second unit is used to obtain the distance between each photovoltaic panel and the depth camera collected by the depth camera above the photovoltaic plant; a third unit, configured to calculate the temperature of each photovoltaic panel based on the infrared radiation intensity and the distance of each photovoltaic panel; wherein, when calculating the temperature, water vapor and carbon dioxide data having a scattering effect on infrared radiation are combined; The fourth unit is used to determine whether there is any abnormality in each photovoltaic panel based on the power generation, temperature and light intensity of each photovoltaic panel; Calculating the temperature of each photovoltaic panel according to the infrared radiation intensity and the distance of each photovoltaic panel includes: Establishing an infrared radiation matrix according to the infrared radiation intensity of each photovoltaic panel collected by the infrared camera; Establishing a distance matrix according to the distance of each photovoltaic panel collected by the depth camera; Determining a coordinate transformation matrix between the infrared camera and the depth camera according to a positional relationship between the infrared camera, the depth camera, and a ground plane; determining a temperature matrix including the temperature of each photovoltaic panel according to the infrared radiation matrix, the distance matrix and the coordinate transformation matrix; The step of determining whether there is an abnormality in each photovoltaic panel based on the power generation, temperature, and light intensity of each photovoltaic panel includes: Establish a detection model based on the normal light intensity, temperature and power generation of photovoltaic panels; Relying on the detection model, it is determined whether there is any abnormality in the photovoltaic panel based on the collected light intensity matrix, temperature matrix and power generation matrix; wherein the power generation matrix includes the power generation of each photovoltaic panel, and the light intensity matrix includes the light intensity of each photovoltaic panel.

7. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, which, when executed in a computer, causes the computer to execute the method according to any one of claims 1 to 5.

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