A smart inspection and maintenance system for photovoltaic power plants

Abstract

This invention relates to the field of visual monitoring technology, and more particularly to an intelligent inspection and maintenance system for photovoltaic power plants. The invention acquires surface point cloud data of each photovoltaic panel through a visual acquisition terminal, and constructs tilt vectors for several rectangular sub-regions and contour vectors for frame contour regions. An intelligent analysis module determines whether the tilt morphology stability of the photovoltaic panel is abnormal based on the results of a first comparison rule, and determines the tilt morphology influence trend based on the results of a second comparison rule. An operation and maintenance management module determines the extraction and analysis parameters for the operation and maintenance data, and determines whether to generate a maintenance work order for the photovoltaic panel based on the analysis results of the extracted and analyzed parameters. Thus, it achieves precise quantification of the tilt morphology of the photovoltaic panel and timely classification of deformation trends for photovoltaic panels with slight deformation trends, improving the scientific nature of data-driven decision-making.

Description

Technical Field

[0001] This invention relates to the field of visual monitoring technology, and in particular to an intelligent inspection and maintenance system for photovoltaic power plants. Background Technology

[0002] During long-term operation, photovoltaic power plants are prone to local or overall deformation of photovoltaic panels due to factors such as material aging, support settlement, and extreme weather, which can lead to reduced light absorption efficiency and problems such as shading and hot spot effects. Traditional inspection methods rely on manual observation or two-dimensional image analysis, which cannot analyze the deformation type and its impact trend in a timely manner. This results in a lack of targeted operation and maintenance strategies and low resource allocation efficiency. At the same time, existing technologies are not able to build scientific operation and maintenance decision-making models, resulting in high operation and maintenance costs. Therefore, there is an urgent need for a high-precision and intelligent inspection and operation and maintenance system.

[0003] For example, Chinese Patent Publication No. CN118247234A discloses a method and system for detecting point hot spots in photovoltaic modules based on local difference measurement. First, a pre-screening segmentation threshold is calculated based on the global grayscale statistics of infrared images to achieve pre-screening of point hot spots. Second, a local block image structure is constructed with each pre-screened pixel as the center, and a local difference measurement is constructed based on the difference in grayscale distribution between the point hot spot and the neighboring background. Then, a secondary screening segmentation threshold is designed based on the constructed local difference measurement to segment the point hot spots. Finally, neighborhood fusion is performed based on the location information of the point hot spot distribution to avoid repeated detection of point hot spots on the same module.

[0004] The following problems still exist in the existing technology:

[0005] Existing technologies cannot accurately quantify the tilt angle of photovoltaic panels, nor can they promptly classify the deformation trends of photovoltaic panels with slight deformation tendencies, affecting the scientific and precise nature of operation and maintenance decisions. Summary of the Invention

[0006] To address this, the present invention provides an intelligent inspection and maintenance system for photovoltaic power plants, which overcomes the problems of existing technologies being unable to accurately quantify the tilt angle of photovoltaic panels and unable to promptly classify the deformation trends of photovoltaic panels with slight deformation tendencies.

[0007] To achieve the above objectives, the present invention provides an intelligent inspection and maintenance system for photovoltaic power plants, comprising:

[0008] The inspection vision acquisition terminal includes a scanning unit and a construction unit. The scanning unit is used to scan the photovoltaic panels and acquire the surface point cloud data of each photovoltaic panel.

[0009] The construction unit constructs the tendency vectors of several rectangular sub-regions and the contour vectors of the frame contour region based on the surface point cloud data.

[0010] The intelligent analysis module is connected to the inspection vision acquisition terminal. It is used to determine whether the tilt shape stability of the photovoltaic panel is abnormal based on the results of several tendency vectors and contour vectors under the first comparison rule, and to determine the tilt shape influence trend of the photovoltaic panel with abnormal tilt shape stability based on the results of several tendency vectors under the second comparison rule.

[0011] The number of vectors involved in the comparison and the position of the rectangular sub-region where the vectors are located are different in the first comparison rule and the second comparison rule;

[0012] The operation and maintenance management module, which is connected to the intelligent analysis module, is used to determine the extraction and analysis parameters of the operation and maintenance data based on the trend of the tilt angle morphology, and to determine whether to generate a maintenance work order for the photovoltaic panel based on the analysis results of the extraction and analysis parameters.

[0013] The extracted and analyzed parameters include the photoelectric conversion efficiency during key influencing periods in historical meteorological data, as well as the temperature distribution differences in each rectangular sub-region.

[0014] Furthermore, the constructing unit is used to construct the tendency vector of the rectangular sub-region, wherein,

[0015] The construction unit obtains the vertex coordinates of each rectangular sub-region, constructs the normal vector of the plane in the plane determined by the vertex coordinates of the rectangular sub-region, and determines the normal vector as the inclination vector of the rectangular sub-region.

[0016] Furthermore, the building unit is used to construct the contour vector of the frame contour region, wherein,

[0017] The construction unit obtains the vertex coordinates of the frame outline region of the photovoltaic panel, constructs the normal vector of the plane in the plane determined by the vertex coordinates of the frame outline region, and determines the normal vector as the outline vector of the frame outline region.

[0018] Furthermore, the intelligent analysis module is used to obtain the results of several tendency vectors and contour vectors under the first comparison rule, wherein,

[0019] The intelligent analysis module determines the vector obtained by adding the tendency vectors of all rectangular sub-regions as the joint representation tendency vector, and determines the vector angle between the joint representation tendency vector and the contour vector as the result of several tendency vectors and contour vectors under the first comparison rule.

[0020] Furthermore, the intelligent analysis module is used to determine whether the tilt angle stability of the photovoltaic panel is abnormal, wherein,

[0021] If the included angle of the vectors does not meet the criteria for determining the stability of the tilt angle, the intelligent analysis module determines that the tilt angle stability of the photovoltaic panel is abnormal.

[0022] The condition for determining the stability of the tilt angle is that the included vector angle does not exceed a preset vector angle threshold.

[0023] Furthermore, in response to the determination result of the abnormal tilt morphology stability of the photovoltaic panel, the intelligent analysis module obtains several tilt vectors under the second comparison rule, wherein...

[0024] The intelligent analysis module filters out several rectangular sub-regions located at the edge of the frame outline region, determines the angle between the tendrils of any two rectangular sub-regions, and determines the standard deviation of the angles as the edge morphology stability.

[0025] The intelligent analysis module filters out several rectangular sub-regions located in non-edge positions within the frame outline region, determines the angle between the tendency vectors of any two rectangular sub-regions within these rectangular sub-regions, and determines the standard deviation of the angles as the non-edge morphological stability.

[0026] The intelligent analysis module determines the absolute value of the difference between the edge morphological stability and the non-edge morphological stability as the result of several tendency vectors under the second comparison rule.

[0027] Furthermore, the intelligent analysis module is used to determine the influence trend of the tilt angle of the photovoltaic panel, wherein,

[0028] If the absolute value of the difference does not exceed the preset difference reference value, the intelligent analysis module determines that the tilt angle of the photovoltaic panel is the first influencing trend of the tilt angle.

[0029] If the absolute value of the difference exceeds the preset difference reference value, the intelligent analysis module determines that the tilt shape influence trend of the photovoltaic panel is the second influence trend of the tilt shape.

[0030] Furthermore, the operation and maintenance management module determines the parameters for extracting and analyzing operation and maintenance data, wherein,

[0031] If the tilt angle of the photovoltaic panel is the first influencing trend, then the extraction and analysis parameter determined by the operation and maintenance management module is the photoelectric conversion efficiency during the key influencing period in the historical meteorological data.

[0032] If the tilt angle of the photovoltaic panel has the second influence trend, then the extraction and analysis parameter determined by the operation and maintenance management module is the temperature distribution difference of each rectangular sub-region during the key influence period in historical meteorological data.

[0033] Furthermore, the operation and maintenance management module is used to determine whether to generate a maintenance work order for the photovoltaic panel based on the photoelectric conversion efficiency, wherein,

[0034] The operation and maintenance management module filters key periods of wind impact based on wind force levels in historical meteorological data, and determines the absolute value of the difference between the photovoltaic panel's photoelectric conversion efficiency and the preset photoelectric conversion efficiency during the key periods of wind impact.

[0035] Based on the result that the absolute value of the efficiency difference exceeds the preset efficiency difference threshold, the operation and maintenance management module determines to generate a maintenance work order for the photovoltaic panel.

[0036] Furthermore, the operation and maintenance management module is used to determine whether to generate a maintenance work order for the photovoltaic panel based on the temperature distribution difference, wherein,

[0037] The operation and maintenance management module filters key periods of light impact based on the light intensity level in historical meteorological data, and determines the standard deviation of surface temperature of each rectangular sub-region of the photovoltaic panel within the key periods of light impact, and determines the standard deviation of surface temperature as the temperature distribution difference.

[0038] Based on the result that the temperature distribution difference exceeds the preset temperature distribution difference threshold, the operation and maintenance management module determines to generate a maintenance work order for the photovoltaic panel.

[0039] Compared with the prior art, the beneficial effects of the present invention are as follows: The present invention acquires surface point cloud data of each photovoltaic panel through a visual acquisition terminal for inspection, and constructs the tilt vector of several rectangular sub-regions and the contour vector of the frame contour region. The intelligent analysis module determines whether the tilt morphology stability of the photovoltaic panel is abnormal according to the results of the first comparison rule and determines the tilt morphology influence trend according to the results of the second comparison rule. The operation and maintenance management module determines the extraction and analysis parameters of the operation and maintenance data, and determines whether to generate a maintenance work order for the photovoltaic panel based on the analysis results of the extraction and analysis parameters. Thus, the tilt morphology of the photovoltaic panel is accurately quantified, and the deformation trend of photovoltaic panels with slight deformation trends is classified in a timely manner, thereby improving the scientific nature of data-driven decision-making.

[0040] Furthermore, this invention constructs normal vectors as tilt vectors and contour vectors by obtaining the vertex coordinates of the rectangular sub-region and the frame contour region. This enables precise description of the directional characteristics of different regions of the photovoltaic panel from a geometric perspective. This vector-based representation method can more accurately capture the tilt angle information of the photovoltaic panel, thereby achieving precise quantification of the tilt angle morphology of the photovoltaic panel.

[0041] Furthermore, the present invention adds the tendency vectors of all rectangular sub-regions to obtain a joint characteristic tendency vector, and then calculates the angle between it and the contour vector. By comparing it with a preset vector angle threshold, the stability of the tilt angle of the photovoltaic panel is determined. This method can comprehensively consider the tendency information of each sub-region of the photovoltaic panel and judge whether the tilt angle of the panel is stable as a whole. Thus, it can realize the timely detection of photovoltaic panels with slight deformation trends.

[0042] Furthermore, this invention categorizes the trend of photovoltaic panel tilt morphology into two types by calculating the absolute value of the difference between edge morphological stability and non-edge morphological stability. When the absolute value of the difference does not exceed the reference value, it is judged as a problem of insufficient fastening force caused by frame looseness; when the difference exceeds the reference value, it is identified as a problem of internal compression and deformation caused by frame deformation. By reflecting the structural changes at different locations through the difference in morphological stability between edge and non-edge positions, the scientific nature of data-driven decision-making is improved.

[0043] Furthermore, under the primary influence of the tilting morphology of photovoltaic panels, this invention prioritizes extracting the photoelectric conversion efficiency during key influencing periods from historical meteorological data. Since wind is a crucial environmental factor affecting the tilting angle and power generation efficiency of photovoltaic panels within a loose framework, by screening key wind-affected periods, a correlation is established between photoelectric conversion efficiency and wind changes, significantly amplifying the impact characteristics of potential structural problems. Based on the comparison of the absolute value of the efficiency difference with a threshold, intelligent generation of maintenance work orders is achieved. For panels with significant impact on power generation efficiency, resources are concentrated for rapid operation and maintenance, improving the utilization efficiency of operation and maintenance resources and enhancing the scientific nature of data-driven decision-making.

[0044] Furthermore, under the second influence trend of the photovoltaic panel exhibiting an angled shape, i.e., when the frame deformation causes internal compression, the internal compression caused by the frame deformation alters the current transmission path of the photovoltaic panel, resulting in an increase in local resistance. Under strong light irradiation, this resistance difference is amplified, forming a significant hot spot effect. By analyzing the temperature standard deviation of each rectangular sub-region during key periods of illumination, this uneven heating phenomenon can be keenly detected. Compared with traditional temperature monitoring methods, this method can more accurately locate subtle temperature anomaly areas. Furthermore, by screening temperature data during periods of high light intensity, the influence of structural anomalies on the temperature field can be effectively amplified, transforming potential frame deformation problems into intuitive temperature difference indicators, achieving correlation diagnosis of structural deformation, and improving the scientific nature of data-driven decision-making. Attached Figure Description

[0045] Figure 1 This is a system block diagram of the intelligent inspection and maintenance system for photovoltaic power plants according to an embodiment of the present invention;

[0046] Figure 2 This is a flowchart illustrating the logic of the intelligent analysis module in this embodiment of the invention for determining whether the stability state of the tilt angle is abnormal.

[0047] Figure 3 A flowchart illustrating the logic of how the intelligent analysis module determines the influence of tilt morphology on trends.

[0048] Figure 4 A flowchart for determining the extraction and analysis parameters for the operation and maintenance management module. Detailed Implementation

[0049] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0050] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0051] It should be noted that in the description of this invention, the terms "upper," "lower," "inner," "outer," etc., which indicate the direction or positional relationship, are based on the direction or positional relationship shown in the drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0052] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation" and "connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0053] Please see Figure 1 The diagram shown is a system block diagram of the intelligent inspection and maintenance system for photovoltaic power plants according to an embodiment of the present invention. The intelligent inspection and maintenance system for photovoltaic power plants of the present invention includes:

[0054] The inspection vision acquisition terminal includes a scanning unit and a construction unit. The scanning unit is used to scan the photovoltaic panels and acquire the surface point cloud data of each photovoltaic panel.

[0055] Specifically, the scanning unit in this invention can be a three-dimensional laser scanner to acquire point cloud data of photovoltaic panels. Three-dimensional laser scanners for acquiring point cloud data of object surfaces are widely used in application scenarios such as three-dimensional modeling, which will not be elaborated here.

[0056] The construction unit constructs the tendency vectors of several rectangular sub-regions and the contour vectors of the frame contour region based on the surface point cloud data.

[0057] Specifically, the building unit in this invention can be an image processor to generate normal vectors for different regions, which will not be elaborated here.

[0058] The intelligent analysis module is connected to the inspection vision acquisition terminal. It is used to determine whether the tilt shape stability of the photovoltaic panel is abnormal based on the results of several tendency vectors and contour vectors under the first comparison rule, and to determine the tilt shape influence trend of the photovoltaic panel with abnormal tilt shape stability based on the results of several tendency vectors under the second comparison rule.

[0059] The number of vectors involved in the comparison and the position of the rectangular sub-region where the vectors are located are different in the first comparison rule and the second comparison rule;

[0060] The operation and maintenance management module, which is connected to the intelligent analysis module, is used to determine the extraction and analysis parameters of the operation and maintenance data based on the trend of the tilt angle morphology, and to determine whether to generate a maintenance work order for the photovoltaic panel based on the analysis results of the extraction and analysis parameters.

[0061] The extracted and analyzed parameters include the photoelectric conversion efficiency during key influencing periods in historical meteorological data, as well as the temperature distribution differences in each rectangular sub-region.

[0062] Specifically, the present invention does not limit the structure of the intelligent analysis module and the operation and maintenance management module. The intelligent analysis module and the operation and maintenance management module can be constructed using logic components, such as field-programmable logic components, microprocessors, processors used in computers, etc., which will not be elaborated here.

[0063] Specifically, the first and second comparison rules can be related algorithms for data analysis and comparison that are pre-stored in the intelligent analysis module, which will not be elaborated here.

[0064] Specifically, the maintenance work order in this invention includes the location information of the photovoltaic panel that needs to be repaired. In practice, the operation and maintenance management module can send the location information of the photovoltaic panel that needs to be repaired to the display terminal for easy viewing by operation and maintenance personnel. The location information can be the pre-set row and column numbers of the photovoltaic panel, which will not be elaborated here.

[0065] Specifically, in this invention, the photoelectric conversion efficiency is calculated as (output electrical power / optical power) × 100%, where the output electrical power is equal to the product of the measured current and voltage, and the optical power is determined by a solar irradiance sensor. The optical power can be determined by the product of the irradiance intensity and the effective area of ​​the photovoltaic panel, with the unit of irradiance being W / m². 2 The unit for the effective area of ​​a photovoltaic panel is m². 2 .

[0066] Specifically, the present invention can use an infrared temperature monitoring instrument to monitor the temperature of the rectangular sub-region, which will not be elaborated here.

[0067] Specifically, the building unit is used to construct the tendency vector of the rectangular sub-region, wherein,

[0068] The construction unit obtains the vertex coordinates of each rectangular sub-region, constructs the normal vector of the plane in the plane determined by the vertex coordinates of the rectangular sub-region, and determines the normal vector as the inclination vector of the rectangular sub-region.

[0069] For example, the rectangular subregion can be divided into two triangular subregions using any diagonal. Based on the vertex coordinates A(x1, y1, z1), B(x2, y2, z2), and C(x3, y3, z3) of the triangle, two vectors are determined with vertex A as the starting point and vertex B and vertex C as the ending points. The normal vector is obtained by performing a cross product operation on the two vectors, which is the normal vector of the triangle. The normal vectors of the two triangular subregions are determined separately. The vector obtained by adding the normal vectors of the two triangular subregions is determined as the yaw vector of the rectangular subregion.

[0070] Specifically, the building unit is used to construct the contour vector of the frame contour region, wherein,

[0071] The construction unit obtains the vertex coordinates of the frame outline region of the photovoltaic panel, constructs the normal vector of the plane in the plane determined by the vertex coordinates of the frame outline region, and determines the normal vector as the outline vector of the frame outline region.

[0072] For example, the frame outline area can be divided into two triangular regions by the diagonal of the entire photovoltaic panel, and the vector obtained by adding the normal vectors of the two triangular regions can be determined as the outline vector of the frame outline area.

[0073] Specifically, this invention constructs normal vectors as tilt vectors and contour vectors by obtaining the vertex coordinates of the rectangular sub-region and the frame contour region. This enables precise description of the directional characteristics of different regions of the photovoltaic panel from a geometric perspective. This vector-based representation method can more accurately capture the tilt angle information of the photovoltaic panel and achieve precise quantification of the tilt angle morphology of the photovoltaic panel.

[0074] Specifically, the intelligent analysis module is used to obtain the results of several tendency vectors and contour vectors under a first comparison rule, wherein,

[0075] The intelligent analysis module determines the vector obtained by adding the tendency vectors of all rectangular sub-regions as the joint representation tendency vector, and determines the vector angle between the joint representation tendency vector and the contour vector as the result of several tendency vectors and contour vectors under the first comparison rule.

[0076] Specifically, please refer to Figure 2 The diagram shown is a flowchart illustrating the logic of the intelligent analysis module in this invention for determining whether the tilt angle stability state is abnormal. The intelligent analysis module is used to determine whether the tilt angle stability state of the photovoltaic panel is abnormal.

[0077] If the included angle of the vectors meets the criteria for determining the stability of the tilt angle, then the intelligent analysis module determines that the tilt angle of the photovoltaic panel is in a stable and normal state.

[0078] If the included angle of the vectors does not meet the criteria for determining the stability of the tilt angle, the intelligent analysis module determines that the tilt angle stability of the photovoltaic panel is abnormal.

[0079] The condition for determining the stability of the tilt angle is that the included vector angle does not exceed a preset vector angle threshold.

[0080] In practice, the preset vector angle threshold can be set by those skilled in the art according to the inspection requirements. If the value of the vector angle threshold is too small, it will cause misjudgment of the difference in photovoltaic panel installation size within the normal range. If the value of the vector angle threshold is too large, it will cause omission of abnormal difference in photovoltaic panel installation size. Based on this, the value range of the vector angle threshold can be [3°, 8°]. Preferably, the value of the vector angle threshold is 5°.

[0081] It is understandable that the building unit obtains the vertex coordinates of the rectangular sub-region to determine a plane. The normal vector of this plane is defined as the tilt vector of the rectangular sub-region. Since the normal vector is perpendicular to the plane, the tilt vector can characterize the directional characteristics of the plane where the rectangular sub-region is located, reflecting the tilt state of the sub-region in space. The contour vector represents the direction of the plane determined by the contour of the entire photovoltaic panel frame. It is a macroscopic representation of the overall tilt state of the photovoltaic panel. If the angle between the vectors actually calculated exceeds the threshold, it indicates that there is a large difference between the local tilt and the overall tilt of the photovoltaic panel, and the tilt angle of the photovoltaic panel is abnormally stable.

[0082] Specifically, this invention adds the tendency vectors of all rectangular sub-regions to obtain a joint characteristic tendency vector, and then calculates the angle between it and the contour vector. By comparing it with a preset vector angle threshold, the stability of the tilt angle of the photovoltaic panel is determined. This method can comprehensively consider the tendency information of each sub-region of the photovoltaic panel and judge whether the tilt angle of the panel is stable as a whole. Thus, it can promptly detect photovoltaic panels with slight deformation trends.

[0083] Specifically, in response to the determination result of the abnormal tilt morphology stability of the photovoltaic panel, the intelligent analysis module obtains several tilt vectors under the second comparison rule, wherein...

[0084] The intelligent analysis module filters out several rectangular sub-regions located at the edge of the frame outline region, determines the angle between the tendrils of any two rectangular sub-regions, and determines the standard deviation of the angles as the edge morphology stability.

[0085] The intelligent analysis module filters out several rectangular sub-regions located in non-edge positions within the frame outline region, determines the angle between the tendency vectors of any two rectangular sub-regions within these rectangular sub-regions, and determines the standard deviation of the angles as the non-edge morphological stability.

[0086] The intelligent analysis module determines the absolute value of the difference between the edge morphological stability and the non-edge morphological stability as the result of several tendency vectors under the second comparison rule.

[0087] Specifically, in this invention, the rectangular sub-regions at the edge of the frame outline region are a ring of rectangular sub-regions along the edge of the frame outline, and the rectangular sub-regions at the non-edge of the frame outline region are all the rectangular sub-regions within the frame outline region except for the ring of rectangular sub-regions along the edge of the frame outline.

[0088] Specifically, please refer to Figure 3 The diagram shown is a flowchart illustrating the logic of how the intelligent analysis module determines the influence of tilt angle morphology on the trend of the photovoltaic panel. This intelligent analysis module is used to determine the influence of tilt angle morphology on the trend of the photovoltaic panel.

[0089] If the absolute value of the difference does not exceed the preset difference reference value, the intelligent analysis module determines that the tilt angle of the photovoltaic panel is the first influencing trend of the tilt angle.

[0090] If the absolute value of the difference exceeds the preset difference reference value, the intelligent analysis module determines that the tilt shape influence trend of the photovoltaic panel is the second influence trend of the tilt shape.

[0091] In practice, the preset range of the difference reference value is [0.3°, 0.8°], and preferably, the difference reference value is 0.5°.

[0092] It is understandable that the frame outline area is divided into rectangular sub-regions at the edge and non-edge positions because the edges of photovoltaic panels are easily affected by environmental stress, while the non-edge areas reflect more internal structural changes. In the second comparison rule, the absolute value of the difference between the stability of the edge and non-edge morphology is compared, which is essentially to judge the degree of difference between the stability of the panel edge and the interior. When the absolute value of the difference does not exceed the preset reference value, it indicates that the stability difference between the edge and non-edge areas is small, that is, the tilt angle change is relatively uniform in the whole panel. When the difference exceeds the reference value, it indicates that the stability difference between the edge and non-edge areas is significant, and there may be local frame deformation, which leads to internal compression and thus causes abnormal internal tilt angle. This achieves effective identification of different types of tilt angle morphological anomalies and their causes.

[0093] Specifically, this invention categorizes the trend of photovoltaic panel tilt morphology into two types by calculating the absolute value of the difference between edge morphological stability and non-edge morphological stability. When the absolute value of the difference does not exceed the reference value, it is judged as a problem of insufficient fastening force caused by frame looseness; when the difference exceeds the reference value, it is identified as a problem of internal compression and deformation caused by frame deformation. By reflecting the structural changes at different locations through the difference in morphological stability between edge and non-edge positions, the scientific nature of data-driven decision-making is improved.

[0094] Specifically, please refer to Figure 4The diagram shown is a logical flowchart of the operation and maintenance management module determining the extraction and analysis parameters. The operation and maintenance management module determines the extraction and analysis parameters for the operation and maintenance data.

[0095] If the tilt angle of the photovoltaic panel is the first influencing trend, then the extraction and analysis parameter determined by the operation and maintenance management module is the photoelectric conversion efficiency during the key influencing period in the historical meteorological data.

[0096] If the tilt angle of the photovoltaic panel has the second influence trend, then the extraction and analysis parameter determined by the operation and maintenance management module is the temperature distribution difference of each rectangular sub-region during the key influence period in historical meteorological data.

[0097] Specifically, the operation and maintenance management module is used to determine whether to generate a maintenance work order for the photovoltaic panel based on the photoelectric conversion efficiency.

[0098] The operation and maintenance management module filters key periods of wind impact based on wind force levels in historical meteorological data, and determines the absolute value of the difference between the photovoltaic panel's photoelectric conversion efficiency and the preset photoelectric conversion efficiency during the key periods of wind impact.

[0099] Based on the result that the absolute value of the efficiency difference exceeds the preset efficiency difference threshold, the operation and maintenance management module determines to generate a maintenance work order for the photovoltaic panel.

[0100] For example, the present invention can screen periods with wind force exceeding level 5 as key wind-affected periods, obtain the photoelectric conversion efficiency of photovoltaic panels with the first influence trend of tilt shape during the key wind-affected periods, and the preset efficiency difference threshold can be the rated conversion efficiency of photovoltaic panels. The value of the preset efficiency difference threshold P0 can be determined according to the rated conversion efficiency P of photovoltaic panels, P0 = δ × P, where δ is the value factor of efficiency difference threshold, and the value range of δ is [0.08, 0.12]. Preferably, the value of δ is 0.1.

[0101] Understandably, when a photovoltaic panel exhibits a tilted shape as its primary influence, its structural stability decreases, making it more sensitive to external environmental factors, such as wind. According to structural mechanics theory, loose frames are more prone to vibration or dynamic changes in tilt angle under wind, which in turn affects the light-receiving angle of the photovoltaic panel. The photovoltaic effect principle shows that changes in the light-receiving angle directly affect the photoelectric conversion efficiency. Therefore, there is an intrinsic relationship between wind and photoelectric conversion efficiency. By screening key periods of wind influence, the amplified impact of environmental factors on unstable structural panels can be captured, revealing potential structural problems through changes in photoelectric efficiency.

[0102] Specifically, this invention prioritizes extracting the photoelectric conversion efficiency during key influencing periods from historical meteorological data, given the primary influence of the tilting shape of photovoltaic panels. Wind is a crucial environmental factor affecting the tilt angle and power generation efficiency of photovoltaic panels within a loose framework. By screening key wind-affected periods, a correlation is established between photoelectric conversion efficiency and wind changes, significantly amplifying the impact characteristics of potential structural problems. Based on the comparison of the absolute value of the efficiency difference with a threshold, intelligent generation of maintenance work orders is achieved. For panels with significant impact on power generation efficiency, resources are concentrated for rapid operation and maintenance, improving the utilization efficiency of operation and maintenance resources and enhancing the scientific nature of data-driven decision-making.

[0103] Specifically, the operation and maintenance management module is used to determine whether to generate a maintenance work order for the photovoltaic panel based on the temperature distribution difference.

[0104] The operation and maintenance management module filters key periods of light impact based on the light intensity level in historical meteorological data, and determines the standard deviation of surface temperature of each rectangular sub-region of the photovoltaic panel within the key periods of light impact, and determines the standard deviation of surface temperature as the temperature distribution difference.

[0105] Based on the result that the temperature distribution difference exceeds the preset temperature distribution difference threshold, the operation and maintenance management module determines to generate a maintenance work order for the photovoltaic panel.

[0106] For example, the present invention can filter the period when the temperature of the photovoltaic panel exceeds 45°C as the critical period of illumination influence, and obtain the temperature distribution difference of the photovoltaic panel in the second influence trend of the tilt shape within the critical period of illumination influence. The value of the preset temperature distribution difference threshold T0 can be determined based on the average temperature T of the photovoltaic panel. m To determine, T0 = ε × T m ε is a factor for the threshold of temperature distribution difference, and the value range of ε is [0.02, 0.1]. Preferably, the value of ε is 0.05.

[0107] Specifically, this invention addresses the second influence trend of photovoltaic panels exhibiting tilt angles, i.e., when frame deformation causes internal compression. This internal compression alters the current transmission path of the photovoltaic panel, leading to increased local resistance. Under strong sunlight, this resistance difference is amplified, resulting in a significant hot spot effect. By analyzing the temperature standard deviation of each rectangular sub-region during key periods of sunlight, this uneven heating phenomenon can be readily detected. Compared to traditional temperature monitoring methods, this method can more accurately locate subtle temperature anomalies. Furthermore, by filtering temperature data during periods of high sunlight intensity, the impact of structural anomalies on the temperature field can be effectively amplified, transforming potential frame deformation problems into intuitive temperature difference indicators. This enables the correlation diagnosis of structural deformation and improves the scientific rigor of data-driven decision-making.

[0108] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0109] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. An intelligent inspection operation and maintenance system for a photovoltaic power station, characterized in that, The method comprises the following steps: a visual acquisition terminal for inspection, comprising a scanning unit and a construction unit, the scanning unit is used to scan photovoltaic panels and obtain surface point cloud data of each photovoltaic panel; the construction unit constructs the inclination vector of each rectangular sub-region and the contour vector of the frame contour region according to the surface point cloud data; an intelligent analysis module connected to the visual acquisition terminal for inspection, used to determine whether the inclination shape stable state of the photovoltaic panel is abnormal according to the results of the comparison of the inclination vector and the contour vector under the first comparison rule, and determine the inclination shape influence trend of the photovoltaic panel with abnormal inclination shape stable state according to the results of the comparison of the inclination vector under the second comparison rule; the number of vectors involved in the comparison and the position of the rectangular sub-region where the vector is located in the first comparison rule and the second comparison rule are different; an operation and maintenance management module connected to the intelligent analysis module, used to determine the extraction analysis parameters of the operation and maintenance data according to the inclination shape influence trend, and determine whether to generate a maintenance work order for the photovoltaic panel according to the analysis results of the extraction analysis parameters; the extraction analysis parameters include the photoelectric conversion efficiency in the key influence period of the historical meteorological data, and the temperature distribution difference of each rectangular sub-region; the intelligent analysis module is used to obtain the results of the comparison of the inclination vector and the contour vector under the first comparison rule, wherein the intelligent analysis module determines the vector obtained by adding the inclination vectors of all rectangular sub-regions as the joint representation inclination vector, and determines the vector included angle between the joint representation inclination vector and the contour vector as the results of the comparison of the inclination vector and the contour vector under the first comparison rule; the intelligent analysis module obtains the results of the comparison of the inclination vector under the second comparison rule in response to the determination result of the inclination shape stable state of the photovoltaic panel being abnormal, wherein the intelligent analysis module selects a plurality of rectangular sub-regions located at the edge position of the frame contour region, determines the included angle between the inclination vectors of any two rectangular sub-regions in the plurality of rectangular sub-regions, and determines the included angle standard deviation of the plurality of included angles as the edge shape stability; the intelligent analysis module selects a plurality of rectangular sub-regions located at the non-edge position of the frame contour region, determines the included angle between the inclination vectors of any two rectangular sub-regions in the plurality of rectangular sub-regions, and determines the included angle standard deviation of the plurality of included angles as the non-edge shape stability; the intelligent analysis module determines the absolute value of the difference between the edge shape stability and the non-edge shape stability as the results of the comparison of the inclination vector under the second comparison rule. 2.The intelligent inspection and operation system for photovoltaic power station according to claim 1, characterized in that, the construction unit is used to construct the inclination vector of the rectangular sub-region, wherein the construction unit obtains the coordinates of the vertices of each rectangular sub-region, constructs the normal vector of the plane determined according to the coordinates of the vertices of the rectangular sub-region, and determines the normal vector as the inclination vector of the rectangular sub-region. 3.The intelligent inspection and operation system for photovoltaic power station according to claim 1, characterized in that, the construction unit is used to construct the contour vector of the frame contour region, wherein The construction unit acquires vertex coordinates of a frame contour region of a photovoltaic panel, constructs a normal vector of a plane determined according to the vertex coordinates of the frame contour region, and determines the normal vector as a contour vector of the frame contour region. 4.The intelligent inspection and operation system for photovoltaic power station according to claim 1, characterized in that, The intelligent analysis module is configured to determine whether an inclination posture stable state of the photovoltaic panel is abnormal. If the vector angle does not meet an inclination posture stable determination condition, the intelligent analysis module determines that the inclination posture stable state of the photovoltaic panel is abnormal. The inclination posture stable determination condition is that the vector angle does not exceed a preset vector angle threshold value. 5.The intelligent inspection and operation system for photovoltaic power station according to claim 1, characterized in that, The intelligent analysis module is configured to determine an inclination posture influence trend of the photovoltaic panel. If the absolute value of the difference does not exceed a preset difference reference value, the intelligent analysis module determines that the inclination posture influence trend of the photovoltaic panel is an inclination posture first influence trend. If the absolute value of the difference exceeds the preset difference reference value, the intelligent analysis module determines that the inclination posture influence trend of the photovoltaic panel is an inclination posture second influence trend. 6.The intelligent inspection and operation system for photovoltaic power station according to claim 5, characterized in that, The operation and maintenance management module determines an extraction analysis parameter of operation and maintenance data. If the inclination posture influence trend of the photovoltaic panel is the inclination posture first influence trend, the operation and maintenance management module determines that the extraction analysis parameter is a photoelectric conversion efficiency in a key influence period in historical meteorological data. If the inclination posture influence trend of the photovoltaic panel is the inclination posture second influence trend, the operation and maintenance management module determines that the extraction analysis parameter is a temperature distribution difference amount of each rectangular sub-region in a key influence period in historical meteorological data. 7.The intelligent inspection and operation system for photovoltaic power station according to claim 6, characterized in that, The operation and maintenance management module is configured to determine whether to generate a repair work order for the photovoltaic panel according to the photoelectric conversion efficiency. The operation and maintenance management module filters a wind key influence period according to a wind level in historical meteorological data, and determines an efficiency difference absolute value of the photoelectric conversion efficiency of the photovoltaic panel in the wind key influence period and a preset photoelectric conversion efficiency. According to a result that the efficiency difference absolute value exceeds a preset efficiency difference threshold value, the operation and maintenance management module determines to generate the repair work order for the photovoltaic panel. 8.The intelligent inspection and operation system for photovoltaic power station according to claim 6, characterized in that, The operation and maintenance management module is configured to determine whether to generate a repair work order for the photovoltaic panel according to the temperature distribution difference amount. The operation and maintenance management module filters a light key influence period according to a light intensity level in historical meteorological data, and determines a surface temperature standard deviation of each rectangular sub-region of the photovoltaic panel in the light key influence period, and determines the surface temperature standard deviation as the temperature distribution difference amount. According to a result that the temperature distribution difference amount exceeds a preset temperature distribution difference threshold value, the operation and maintenance management module determines to generate the repair work order for the photovoltaic panel.

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