Artificial intelligence system based on panoramic smart energy cloud edge collaboration

Abstract

The invention discloses an artificial intelligence system based on panoramic smart energy cloud edge collaboration, which belongs to the technical field of artificial intelligence and comprises a data acquisition module, a longitudinal tilt state characterization parameter acquisition module, a transverse tilt state characterization parameter acquisition module and a cloud processing module. According to the method, the longitudinal inclination state of the current photovoltaic panel can be accurately represented through the y-axis direction center point spacing difference value, and meanwhile, the transverse inclination state of the current photovoltaic panel can be accurately represented through the x-axis direction center point spacing difference value, so that the longitudinal and transverse inclination angles of the photovoltaic panel can be conveniently and accurately adjusted subsequently; and according to the longitudinal and transverse inclination states of the photovoltaic panel, the corresponding inclination angle adjustment value and the corresponding adjustment direction can be accurately obtained, and the angle adjustment work of the photovoltaic panel is completed by adopting a cloud-edge cooperation mode, so that the photovoltaic panel directly faces the sun, and the productivity efficiency of the photovoltaic panel is improved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and particularly to an artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration. Background Art

[0002] A panoramic intelligent energy system is a comprehensive energy solution that deeply integrates energy management with advanced information technology and intelligent technology to achieve all-round, full-process monitoring, control, optimization, and management of the energy system, aiming to improve energy output and utilization efficiency, ensure energy security, and promote sustainable energy development. The panoramic intelligent energy system can deeply mine and analyze the massive energy data collected by means of big data analysis, artificial intelligence, machine learning, etc. It can not only discover potential problems and abnormal situations in the energy system, but also predict energy demand, equipment failures, etc., providing a scientific basis for decision-making.

[0003] Based on the results of intelligent analysis, the panoramic intelligent energy system can precisely regulate the equipment and facilities in the energy system through an advanced control system. How to adopt the cloud-edge collaboration method to adjust the angle of photovoltaic panels in the solar power generation scenario, thereby effectively improving the production efficiency, is an urgent problem to be solved. For this reason, an artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration is proposed. Summary of the Invention

[0004] The technical problem to be solved by the present invention is: how to adopt the cloud-edge collaboration method to adjust the angle of photovoltaic panels in the solar power generation scenario, thereby effectively improving the production efficiency, and an artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration is provided.

[0005] The present invention solves the above technical problem through the following technical solutions. The present invention includes a data acquisition module, a longitudinal tilt state characterization parameter acquisition module, a transverse tilt state characterization parameter acquisition module, and a cloud processing module;

[0006] The data acquisition module is used to acquire sky images captured by four cameras arranged around the current photovoltaic panel;

[0007] The longitudinal tilt state characterization parameter acquisition module is used to perform recognition processing on the sky image to obtain the longitudinal tilt state characterization parameter and the corresponding comparison result;

[0008] The transverse tilt state characterization parameter acquisition module is used to perform recognition processing on the sky image to obtain the transverse tilt state characterization parameter and the corresponding comparison result;

[0009] The cloud processing module is configured to receive the longitudinal tilt state characterization parameter, the transverse tilt state characterization parameter, and the corresponding comparison result, obtain the longitudinal tilt angle adjustment value and the transverse tilt angle adjustment value of the current photovoltaic panel, and send them to the corresponding adjustment components.

[0010] Further, in the data acquisition module, the four cameras are respectively a first camera, a second camera, a third camera, and a fourth camera; the first camera, the second camera, the third camera, and the fourth camera all capture images in front of the photovoltaic panel to respectively obtain a first sky image, a second sky image, a third sky image, and a fourth sky image; the first camera and the third camera are symmetrically arranged at a set distance above and below the photovoltaic panel, the second camera and the fourth camera are symmetrically arranged at a set distance on both sides of the photovoltaic panel, the optical axes of the first camera, the second camera, the third camera, and the fourth camera are all perpendicular to the front end face of the photovoltaic panel, and the optical axes of the first camera and the third camera intersect with the longitudinal center line of the front end face of the photovoltaic panel, and the optical axes of the second camera and the fourth camera intersect with the transverse center line of the front end face of the photovoltaic panel; the sizes and resolutions of the sky images obtained by the first camera, the second camera, the third camera, and the fourth camera are all the same; wherein, the sky images include the complete sun.

[0011] Further, the longitudinal tilt state characterization parameter acquisition module includes a first image recognition unit, a first image superimposing unit, and a longitudinal tilt state characterization parameter acquisition unit; the first image recognition unit is configured to identify the first sky image and the third sky image obtained by the first camera and the third camera through a trained object detection model to obtain the position information of the solar object detection frames in the two sky images; the first image superimposing unit is configured to superimpose the first sky image and the third sky image, and when superimposing, increase the transparency of the areas outside the solar object detection frames in the first sky image and the third sky image to 100%, so that both solar objects in the generated first superimposed image can be clearly displayed, and the pixel positions in the first superimposed image correspond one by one to those in the first sky image and the third sky image; the longitudinal tilt state characterization parameter acquisition unit is configured to obtain the longitudinal tilt state characterization parameter according to the position information of the two solar object detection frames in the first superimposed image.

[0012] Further, in the longitudinal tilt state characterization parameter acquisition unit, the specific processing process is as follows:

[0013] S11: Obtain the position information of the solar target detection frames in the two sky images collected by the first camera and the third camera, and use the position information of the solar target detection frames in the two sky images as the position information of the two solar target detection frames in the first composite image; wherein, the first composite image corresponds one-to-one with the pixel positions in the first sky image and the third sky image, and the position information is the coordinates of the upper left corner point and the lower right corner point of the target detection frame in the image.

[0014] S12: Calculate the center point coordinates of the two solar target detection frames in the first composite image based on the position information of the two solar target detection frames in the first composite image. The center points of the two solar target detection frames are denoted as CZ1 and CZ2.

[0015] S13: Read the center point coordinates of the first composite image, and denote the center point of the first composite image as OZ1.

[0016] S14: Calculate the y-axis coordinate differences between the center points CZ1 and CZ2 of the two solar target detection frames and the center point OZ1 of the first composite image, and denote them as Dy1 and Dy2 respectively. Among them, Dy1 is the y-axis coordinate difference between the center point CZ1 of the upper solar target detection frame and the center point OZ1 in the first composite image, and Dy2 is the y-axis coordinate difference between the center point CZ2 of the lower solar target detection frame and the center point OZ1 in the first composite image; the center point OZ1 of the first composite image is located between the center points CZ1 and CZ2 of the two solar target detection frames.

[0017] S15: Calculate the difference between Dy1 and Dy2 and compare their magnitudes, and denote this difference as the center point spacing difference B1 in the y-axis direction. The center point spacing difference B1 in the y-axis direction is the longitudinal tilt state characterization parameter.

[0018] Furthermore, the horizontal tilt state characterization parameter acquisition module includes a second image recognition unit, a second image composite unit, and a horizontal tilt state characterization parameter acquisition unit; the second image recognition unit is used to identify the second sky image and the fourth sky image obtained by the second camera and the fourth camera through the target detection model, and obtain the position information of the solar target detection frames in the sky images; the second image composite unit is used to composite the second sky image and the fourth sky image, and increase the transparency of the areas outside the solar target detection frames in the second sky image and the fourth sky image to 100% during the composite process, so that both solar targets in the generated second composite image can be clearly displayed. The second composite image corresponds one-to-one with the pixel positions in the second sky image and the fourth sky image; the horizontal tilt state characterization parameter acquisition unit is used to obtain the horizontal tilt state characterization parameter according to the position information of the two solar target detection frames in the second composite image.

[0019] Further, in the horizontal tilt state characterization parameter acquisition unit, the specific processing process is as follows:

[0020] S21: Obtain the position information of the solar target detection frames in the two sky images collected by the second camera and the fourth camera, and use the position information of the solar target detection frames in the two sky images as the position information of the two solar target detection frames in the second composite image; wherein, the second composite image corresponds one-to-one with the pixel positions in the second sky image and the fourth sky image;

[0021] S22: Calculate the center point coordinates of the two solar target detection frames in the second composite image according to the position information of the two solar target detection frames in the second composite image. The center points of the two solar target detection frames are denoted as CH1 and CH2;

[0022] S23: Read the center point coordinates of the second composite image, and denote the center point of the first composite image as OH1;

[0023] S24: Calculate the x-axis coordinate differences between the center points CH1 and CH2 of the two solar target detection frames and the center point OH1 of the second composite image, and denote them as Dx1 and Dx2 respectively. Among them, Dx1 is the x-axis coordinate difference between the center point CH1 of the right solar target detection frame and the center point OH1 in the second composite image, and Dx2 is the x-axis coordinate difference between the center point CH1 of the left solar target detection frame and the center point OH1 in the second composite image; The center point OH1 of the second composite image is located between the center points CH1 and CH2 of the two solar target detection frames;

[0024] S25: Calculate the difference between Dx1 and Dx2 and compare their magnitudes, and denote this difference as the center point spacing difference B2 in the x-axis direction. The center point spacing difference B2 in the x-axis direction is the horizontal tilt state characterization parameter.

[0025] Further, in the cloud processing module, the specific processing process is as follows:

[0026] S31: Obtain the center point spacing difference B1 in the y-axis direction and the comparison result of the magnitudes of Dy1 and Dy2 in step S15, and at the same time obtain the center point spacing difference B2 in the x-axis direction and the comparison result of the magnitudes of Dx1 and Dx2 in step S25;

[0027] [[ID=

[0028] S33: Determine the positive or negative sign of the longitudinal tilt angle adjustment value Jz according to the comparison result of the magnitudes of Dy1 and Dy2. When Dy1 is greater than Dy2, the longitudinal tilt angle adjustment value Jz is negative, that is, reduce the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z-axis in the space coordinate system. When Dy1 is less than Dy2, the longitudinal tilt angle adjustment value Jz is positive, that is, increase the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z-axis in the space coordinate system. At the same time, determine the positive or negative sign of the transverse tilt angle adjustment value Jh according to the comparison result of the magnitudes of Dx1 and Dx2. When Dx1 is less than Dx2, the transverse tilt angle adjustment value Jh is negative, that is, reduce the angle between the transverse center line of the front end face of the photovoltaic panel and the positive direction of the X-axis in the space coordinate system. When Dy1 is greater than Dy2, the transverse tilt angle adjustment value Jh is positive, that is, increase the angle between the transverse center line of the front end face of the photovoltaic panel and the positive direction of the x-axis in the space coordinate system. When Dy1 is equal to Dy2, the longitudinal tilt angle adjustment value Jz is zero. When Dy1 is equal to Dy2, the transverse tilt angle adjustment value Jh is zero, and no adjustment is performed.

[0029] S34: Send the longitudinal tilt angle adjustment value Jz and the transverse tilt angle adjustment value Jh including positive and negative attributes to the longitudinal tilt angle adjustment component and the transverse tilt angle adjustment component to adjust the longitudinal tilt angle and the transverse tilt angle of the photovoltaic panel, so as to make the photovoltaic panel face the sun directly.

[0030] Furthermore, in the step S32, the y-axis direction center point spacing difference - longitudinal tilt angle adjustment value database stores the corresponding relationship between the y-axis direction center point spacing difference and the longitudinal tilt angle adjustment value; the x-axis direction center point spacing difference - transverse tilt angle adjustment value database stores the corresponding relationship between the x-axis direction center point spacing difference and the transverse tilt angle adjustment value.

[0031] Furthermore, in the step S4, the longitudinal tilt angle of the photovoltaic panel refers to the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z-axis in the space coordinate system, and the transverse tilt angle of the photovoltaic panel refers to the angle between the transverse center line of the front end face of the photovoltaic panel and the positive direction of the X-axis in the space coordinate system. Among them, the X-axis and Y-axis in the space coordinate system are located on the ground, the Z-axis is vertically upward, and the three axes are perpendicular to each other.

[0032] The present invention has the following advantages compared with the prior art: The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration can accurately characterize the longitudinal tilt state of the current photovoltaic panel through the difference in the center point spacing in the y-axis direction, and at the same time can accurately characterize the transverse tilt state of the current photovoltaic panel through the difference in the center point spacing in the x-axis direction, which is convenient for accurately adjusting the longitudinal and transverse tilt angles of the photovoltaic panel subsequently; and can accurately obtain the corresponding tilt angle adjustment value and the corresponding adjustment direction according to the longitudinal and transverse tilt states of the photovoltaic panel, and adopts the cloud-edge collaboration method to complete the angle adjustment work of the photovoltaic panel, making the photovoltaic panel face the sun directly and improving the production efficiency of the photovoltaic panel. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a schematic structural diagram of the artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration in an embodiment of the present invention;

[0034] Figure 2 is a schematic diagram of the positions of the cameras around the photovoltaic panel in an embodiment of the present invention (here, the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z-axis of the space coordinate system is zero, and the angle between the transverse center line and the positive direction of the X-axis of the space coordinate system is zero);

[0035] Figure 3 is a schematic diagram of the first superimposed image in an embodiment of the present invention;

[0036] Figure 4 is a schematic diagram of the second superimposed image in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] The following will describe in detail the embodiments of the present invention. The embodiments are implemented on the premise of the technical solution of the present invention, and detailed implementation manners and specific operation processes are given. However, the protection scope of the present invention is not limited to the following embodiments.

[0038] As Figure 1 shown, this embodiment provides a technical solution: an artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration. In this embodiment, a single photovoltaic panel is taken as an example for illustration. The artificial intelligence system includes a data acquisition module, a longitudinal tilt state characterization parameter acquisition module, a transverse tilt state characterization parameter acquisition module, and a cloud processing module; among them, the data acquisition module is set in the edge device, and the longitudinal tilt state characterization parameter acquisition module, the transverse tilt state characterization parameter acquisition module, and the cloud processing module are all set in the cloud and are used for calculating and processing relevant data. In this way, only the corresponding data needs to be collected on the edge device, greatly reducing the hardware complexity of the edge device.

[0039] In this embodiment, the data acquisition module is used to acquire the sky images captured by four cameras arranged around the current photovoltaic panel.

[0040] More specifically, the data acquisition module includes a first shooting unit and a second shooting unit; the first shooting unit shoots the front of the photovoltaic panel through four cameras arranged around the photovoltaic panel to obtain corresponding sky images.

[0041] As Figure 2 shown, in the data acquisition module, the four cameras are respectively a first camera 11, a second camera 12, a third camera 13, and a fourth camera 14; the first camera 11, the second camera 12, the third camera 13, and the fourth camera 14 all shoot the front of the photovoltaic panel to obtain a first sky image, a second sky image, a third sky image, and a fourth sky image respectively; the first camera 11 and the third camera 13 are symmetrically arranged at a set distance above and below the photovoltaic panel, the second camera 12 and the fourth camera 14 are symmetrically arranged at a set distance on both sides of the photovoltaic panel, the optical axes of the first camera 11, the second camera 12, the third camera 13, and the fourth camera 14 are all perpendicular to the front end face of the photovoltaic panel, and the optical axes of the first camera 11 and the third camera 13 intersect with the longitudinal center line of the front end face of the photovoltaic panel, and the optical axes of the second camera 12 and the fourth camera 14 intersect with the transverse center line of the front end face of the photovoltaic panel; the sizes and resolutions of the sky images obtained by the first camera 11, the second camera 12, the third camera 13, and the fourth camera 14 are all the same; among them, the sky image includes a complete sun.

[0042] In this embodiment, the longitudinal tilt state characterization parameter acquisition module is used to perform recognition processing according to the sky image to obtain the longitudinal tilt state characterization parameter and the corresponding comparison result.

[0043] More specifically, the longitudinal tilt state characterization parameter acquisition module includes a first image recognition unit, a first image superposition unit, and a longitudinal tilt state characterization parameter acquisition unit; the first image recognition unit is used to recognize the first sky image and the third sky image obtained by the first camera 11 and the third camera 13 through a trained target detection model to obtain the position information of the solar target detection frames in the two sky images; the first image superposition unit is used to superpose the first sky image and the third sky image, and when superposing, increase the transparency of the areas outside the solar target detection frames in the first sky image and the third sky image to 100%, so that both of the two solar targets in the generated first superposed image (see Figure 3 ) can be clearly displayed, and the pixel positions in the first superposed image correspond one by one to those in the first sky image and the third sky image; the longitudinal tilt state characterization parameter acquisition unit is used to obtain the longitudinal tilt state characterization parameter according to the position information of the two solar target detection frames in the first superposed image.

[0044] More specifically, in the first image recognition unit, the object detection model is trained based on the SSD object detection network.

[0045] More specifically, in the unit for obtaining the longitudinal tilt state characterization parameter, the specific processing procedure is as follows:

[0046] S11: Obtain the position information of the solar object detection frames in the two sky images collected by the first camera 11 and the third camera 13, and use the position information of the solar object detection frames in the two sky images as the position information of the two solar object detection frames in the first superimposed image; wherein, the first superimposed image corresponds one-to-one with the pixel positions in the first sky image and the third sky image, and the position information is the coordinates of the upper left corner point and the lower right corner point of the object detection frame in the image.

[0047] S12: Calculate the center point coordinates of the two solar object detection frames in the first superimposed image according to the position information of the two solar object detection frames in the first superimposed image. The center points of the two solar object detection frames are denoted as CZ1 and CZ2.

[0048] S13: Read the center point coordinates of the first superimposed image, and denote the center point of the first superimposed image as OZ1.

[0049] S14: Calculate the y-axis coordinate differences between the center points CZ1 and CZ2 of the two solar object detection frames and the center point OZ1 of the first superimposed image, and denote them as Dy1 and Dy2 respectively. Among them, Dy1 is the y-axis coordinate difference between the center point CZ1 of the upper solar object detection frame and the center point OZ1 in the first superimposed image, and Dy2 is the y-axis coordinate difference between the center point CZ1 of the lower solar object detection frame and the center point OZ1 in the first superimposed image; the center point OZ1 of the first superimposed image is located between the center points CZ1 and CZ2 of the two solar object detection frames.

[0050] S15: Calculate the difference between Dy1 and Dy2 and compare their magnitudes, and denote this difference as the center point spacing difference B1 in the y-axis direction. The center point spacing difference B1 in the y-axis direction is the longitudinal tilt state characterization parameter.

[0051] In the present invention, the longitudinal tilt state of the current photovoltaic panel can be accurately characterized by the center point spacing difference in the y-axis direction, which is convenient for accurately adjusting the longitudinal tilt angle of the photovoltaic panel subsequently.

[0052] It should be noted that the longitudinal tilt angle of the photovoltaic panel in this embodiment refers to the angle between the longitudinal center line and the positive direction of the Z-axis in the space coordinate system. In the space coordinate system of this embodiment, the X-axis and the Y-axis are located on the ground and are perpendicular to each other, and the Z-axis is vertically upward.

[0053] In this embodiment, the lateral tilt state characterization parameter acquisition module is configured to perform recognition processing on the sky image to obtain the lateral tilt state characterization parameter and the corresponding comparison result.

[0054] More specifically, the lateral tilt state characterization parameter acquisition module includes a second image recognition unit, a second image superposition unit, and a lateral tilt state characterization parameter acquisition unit; the second image recognition unit is configured to recognize the second sky image and the fourth sky image obtained by the second camera 12 and the fourth camera 14 through the target detection model, and obtain the position information of the solar target detection frame in the sky image; the second image superposition unit is configured to superpose the second sky image and the fourth sky image, and increase the transparency of the area outside the solar target detection frame in the second sky image and the fourth sky image to 100% during superposition, so that both solar targets in the generated second superposed image (see Figure 4 ) can be clearly displayed, and the pixel positions in the second superposed image, the second sky image, and the fourth sky image correspond one by one; the lateral tilt state characterization parameter acquisition unit is configured to obtain the lateral tilt state characterization parameter according to the position information of the two solar target detection frames in the second superposed image.

[0055] More specifically, in the lateral tilt state characterization parameter acquisition unit, the specific processing process is as follows:

[0056] S21: Obtain the position information of the solar target detection frames in the two sky images collected by the second camera 12 and the fourth camera 14, and use the position information of the solar target detection frames in the two sky images as the position information of the two solar target detection frames in the second superposed image; wherein, the pixel positions in the second superposed image, the second sky image, and the fourth sky image correspond one by one;

[0057] S22: Calculate the center point coordinates of the two solar target detection frames in the second superposed image according to the position information of the two solar target detection frames in the second superposed image, and the center points of the two solar target detection frames are denoted as CH1 and CH2;

[0058] S23: Read the center point coordinates of the second superposed image, and denote the center point of the first superposed image as OH1;

[0059] S24: Calculate the x-axis coordinate differences between the center points CH1 and CH2 of the two solar target detection frames and the center point OH1 of the second superimposed image, denoted as Dx1 and Dx2 respectively. Here, Dx1 is the x-axis coordinate difference between the center point CH1 of the right solar target detection frame and the center point OH1 in the second superimposed image, and Dx2 is the x-axis coordinate difference between the center point CH1 of the left solar target detection frame and the center point OH1 in the second superimposed image; the center point OH1 of the second superimposed image is located between the center points CH1 and CH2 of the two solar target detection frames.

[0060] S25: Calculate the difference between Dx1 and Dx2 and compare their magnitudes. Denote this difference as the center point spacing difference B2 in the x-axis direction. The center point spacing difference B2 in the x-axis direction is the lateral tilt state characterization parameter.

[0061] In the present invention, the lateral tilt state of the current photovoltaic panel can be accurately characterized by the center point spacing difference in the x-axis direction, which facilitates the subsequent precise adjustment of the lateral tilt angle of the photovoltaic panel.

[0062] It should be noted that the longitudinal tilt angle of the photovoltaic panel in this embodiment refers to the angle between the lateral center line and the positive direction of the X-axis in the space coordinate system.

[0063] In this embodiment, the cloud processing module is used to receive the longitudinal tilt state characterization parameter, the lateral tilt state characterization parameter, and the corresponding comparison results, obtain the longitudinal tilt angle adjustment value and the lateral tilt angle adjustment value of the current photovoltaic panel, and send them to the corresponding adjustment components.

[0064] More specifically, in the cloud processing module, the specific processing process is as follows:

[0065] S31: Obtain the center point spacing difference B1 in the y-axis direction and the comparison result of the magnitudes of Dy1 and Dy2 in step S15, and at the same time obtain the center point spacing difference B2 in the x-axis direction and the comparison result of the magnitudes of Dx1 and Dx2 in step S25.

[0066] S32: Search and compare according to the center point spacing difference B1 in the y-axis direction in the preset y-axis direction center point spacing difference - longitudinal tilt angle adjustment value database to obtain the longitudinal tilt angle adjustment value Jz corresponding to the center point spacing difference B1 in the y-axis direction; search and compare according to the center point spacing difference B2 in the x-axis direction in the preset x-axis direction center point spacing difference - lateral tilt angle adjustment value database to obtain the lateral tilt angle adjustment value Jh corresponding to the center point spacing difference B2 in the x-axis direction.

[0067] S33: Determine the sign of the longitudinal tilt angle adjustment value Jz based on the comparison result of Dy1 and Dy2. When Dy1 is greater than Dy2, the longitudinal tilt angle adjustment value Jz is negative, that is, reduce the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z-axis in the space coordinate system. When Dy1 is less than Dy2, the longitudinal tilt angle adjustment value Jz is positive, that is, increase the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z-axis in the space coordinate system. At the same time, determine the sign of the transverse tilt angle adjustment value Jh based on the comparison result of Dx1 and Dx2. When Dx1 is less than Dx2, the transverse tilt angle adjustment value Jh is negative, that is, reduce the angle between the transverse center line of the front end face of the photovoltaic panel and the positive direction of the X-axis in the space coordinate system. When Dy1 is greater than Dy2, the transverse tilt angle adjustment value Jh is positive, that is, increase the angle between the transverse center line of the front end face of the photovoltaic panel and the positive direction of the x-axis in the space coordinate system. When Dy1 is equal to Dy2, the longitudinal tilt angle adjustment value Jz is zero. When Dy1 is equal to Dy2, the transverse tilt angle adjustment value Jh is zero, and no adjustment is performed.

[0068] S34: Send the longitudinal tilt angle adjustment value Jz and the transverse tilt angle adjustment value Jh with positive and negative attributes to the longitudinal tilt angle adjustment component and the transverse tilt angle adjustment component to adjust the longitudinal tilt angle and the transverse tilt angle of the photovoltaic panel, so as to make the photovoltaic panel face the sun.

[0069] More specifically, in the y-axis direction center point spacing difference - longitudinal tilt angle adjustment value database, there is a corresponding relationship between the y-axis direction center point spacing difference and the longitudinal tilt angle adjustment value; in the x-axis direction center point spacing difference - transverse tilt angle adjustment value database, there is a corresponding relationship between the x-axis direction center point spacing difference and the transverse tilt angle adjustment value.

[0070] It should be noted that both the longitudinal tilt angle adjustment component and the transverse tilt angle adjustment component drive the rotating shaft through the corresponding motor to realize the angle adjustment work of the photovoltaic panel. Both the longitudinal tilt angle adjustment component and the transverse tilt angle adjustment component are arranged in the edge device.

[0071] It should be noted that in this embodiment, the data acquisition module takes corresponding images regularly, and then adjusts the angle of the photovoltaic panel regularly. It is mainly applicable to photovoltaic power generation areas with long sunshine time and many sunny days. When the sun target is not captured in the image at a certain moment, the adjustment is made according to the angle mode of the photovoltaic panel at the same moment of the previous day.

[0072] In summary, the artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration in the above embodiments can accurately characterize the longitudinal tilt state of the current photovoltaic panel through the difference in the center point spacing in the y-axis direction, and at the same time can accurately characterize the transverse tilt state of the current photovoltaic panel through the difference in the center point spacing in the x-axis direction, facilitating the subsequent precise adjustment of the longitudinal and transverse tilt angles of the photovoltaic panel; and can accurately obtain the corresponding tilt angle adjustment value and the corresponding adjustment direction according to the longitudinal and transverse tilt states of the photovoltaic panel, and adopts the cloud-edge collaboration method to complete the angle adjustment work of the photovoltaic panel, making the photovoltaic panel face the sun directly and improving the production efficiency of the photovoltaic panel.

[0073] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, "a plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0074] In the description of this specification, the description referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0075] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. An artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration, characterized in that, Including: A data acquisition module, a longitudinal tilt state characterization parameter acquisition module, a lateral tilt state characterization parameter acquisition module, and a cloud processing module; The data acquisition module is used to acquire sky images captured by four cameras arranged around the current photovoltaic panel; The longitudinal tilt state characterization parameter acquisition module is used to perform recognition processing based on the sky images to acquire longitudinal tilt state characterization parameters and corresponding comparison results; The lateral tilt state characterization parameter acquisition module is used to perform recognition processing based on the sky images to acquire lateral tilt state characterization parameters and corresponding comparison results; The cloud processing module is used to receive the longitudinal tilt state characterization parameters, the lateral tilt state characterization parameters, and the corresponding comparison results, acquire the longitudinal tilt angle adjustment value and the lateral tilt angle adjustment value of the current photovoltaic panel, and send them to the corresponding adjustment components.

2. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 1, wherein, In the data acquisition module, the four cameras are respectively the first camera, the second camera, the third camera, and the fourth camera; the first camera, the second camera, the third camera, and the fourth camera all capture the front of the photovoltaic panel to respectively acquire the first sky image, the second sky image, the third sky image, and the fourth sky image; the first camera and the third camera are symmetrically arranged at a set distance above and below the photovoltaic panel, the second camera and the fourth camera are symmetrically arranged at a set distance on both sides of the photovoltaic panel, the optical axes of the first camera, the second camera, the third camera, and the fourth camera are all perpendicular to the front end face of the photovoltaic panel, and the optical axes of the first camera and the third camera intersect with the longitudinal center line of the front end face of the photovoltaic panel, and the optical axes of the second camera and the fourth camera intersect with the lateral center line of the front end face of the photovoltaic panel; the sizes and resolutions of the sky images acquired by the first camera, the second camera, the third camera, and the fourth camera are all the same; wherein, the sky images include the complete sun.

3. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 2, wherein, The longitudinal tilt state characterization parameter acquisition module includes a first image recognition unit, a first image overlay unit, and a longitudinal tilt state characterization parameter acquisition unit; the first image recognition unit is used to recognize the first sky image and the third sky image acquired by the first camera and the third camera through a trained object detection model to acquire the position information of the solar object detection frames in the two sky images; The first image overlay unit is used to overlay the first sky image and the third sky image, and when overlaying, increase the transparency of the areas outside the solar object detection frames in the first sky image and the third sky image to 100%, so that both solar objects in the generated first overlay image can be clearly displayed, and the first overlay image corresponds one-to-one with the pixel positions in the first sky image and the third sky image; the longitudinal tilt state characterization parameter acquisition unit is used to acquire longitudinal tilt state characterization parameters according to the position information of the two solar object detection frames in the first overlay image.

4. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 3, wherein In the longitudinal tilt state characterization parameter acquisition unit, the specific processing process is as follows: S11: Obtain the position information of the solar target detection frames in the two sky images captured by the first camera and the third camera, and use the position information of the solar target detection frames in the two sky images as the position information of the two solar target detection frames in the first composite image. Among them, the first composite image corresponds one-to-one with the pixel positions in the first sky image and the third sky image, and the position information is the coordinates of the upper left corner point and the lower right corner point of the target detection frame in the image. S12: Calculate the center point coordinates of the two solar target detection frames in the first composite image according to the position information of the two solar target detection frames in the first composite image. The center points of the two solar target detection frames are denoted as CZ1 and CZ2. S13: Read the center point coordinates of the first composite image, and denote the center point of the first composite image as OZ1. S14: Calculate the y-axis coordinate differences between the center points CZ1 and CZ2 of the two solar target detection frames and the center point OZ1 of the first composite image, and denote them as Dy1 and Dy2 respectively. Among them, Dy1 is the y-axis coordinate difference between the center point CZ1 of the upper solar target detection frame in the first composite image and the center point OZ1, and Dy2 is the y-axis coordinate difference between the center point CZ1 of the lower solar target detection frame in the first composite image and the center point OZ1. The center point OZ1 of the first composite image is located between the center points CZ1 and CZ2 of the two solar target detection frames. S15: Calculate the difference between Dy1 and Dy2 and compare their magnitudes, and denote this difference as the center point spacing difference B1 in the y-axis direction. The center point spacing difference B1 in the y-axis direction is the longitudinal tilt state characterization parameter.

5. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 4, characterized in that, The horizontal tilt state characterization parameter acquisition module includes a second image recognition unit, a second image composite unit, and a horizontal tilt state characterization parameter acquisition unit. The second image recognition unit is used to identify the second sky image and the fourth sky image obtained by the second camera and the fourth camera through the target detection model, and obtain the position information of the solar target detection frames in the sky images. The second image composite unit is used to composite the second sky image and the fourth sky image. When compositing, increase the transparency of the areas outside the solar target detection frames in the second sky image and the fourth sky image to 100%, so that both solar targets in the generated second composite image can be clearly displayed. The second composite image corresponds one-to-one with the pixel positions in the second sky image and the fourth sky image. The horizontal tilt state characterization parameter acquisition unit is used to obtain the horizontal tilt state characterization parameter according to the position information of the two solar target detection frames in the second composite image.

6. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 5, wherein, In the horizontal tilt state characterization parameter acquisition unit, the specific processing process is as follows: S21: Obtain the position information of the solar target detection frames in the two sky images captured by the second camera and the fourth camera, and use the position information of the solar target detection frames in the two sky images as the position information of the two solar target detection frames in the second composite image. Among them, the second composite image corresponds one-to-one with the pixel positions in the second sky image and the fourth sky image. S22: Calculate the center point coordinates of the two solar target detection boxes in the second superimposed image based on the position information of the two solar target detection boxes in the second superimposed image. Denote the center points of the two solar target detection boxes as CH1 and CH2; S23: Read the center point coordinates of the second superimposed image, and denote the center point of the first superimposed image as OH1; S24: Calculate the x-axis coordinate differences between the center points CH1 and CH2 of the two solar target detection boxes and the center point OH1 of the second superimposed image, and denote them as Dx1 and Dx2 respectively. Among them, Dx1 is the x-axis coordinate difference between the center point CH1 of the right solar target detection box in the second superimposed image and the center point OH1, and Dx2 is the x-axis coordinate difference between the center point CH1 of the left solar target detection box in the second superimposed image and the center point OH1; The center point OH1 of the second superimposed image is located between the center points CH1 and CH2 of the two solar target detection boxes; S25: Calculate the difference between Dx1 and Dx2 and compare their magnitudes. Denote this difference as the center point spacing difference B2 in the x-axis direction. The center point spacing difference B2 in the x-axis direction is the horizontal tilt state characterization parameter.

7. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 6, characterized in that, In the cloud processing module, the specific processing process is as follows: S31: Obtain the center point spacing difference B1 in the y-axis direction and the comparison result of the magnitudes of Dy1 and Dy2 in step S15, and at the same time obtain the center point spacing difference B2 in the x-axis direction and the comparison result of the magnitudes of Dx1 and Dx2 in step S25; S32: Look up and compare according to the center point spacing difference B1 in the y-axis direction in the preset y-axis center point spacing difference - longitudinal tilt angle adjustment value database to obtain the longitudinal tilt angle adjustment value Jz corresponding to the center point spacing difference B1 in the y-axis direction; Look up and compare according to the center point spacing difference B2 in the x-axis direction in the preset x-axis center point spacing difference - horizontal tilt angle adjustment value database to obtain the horizontal tilt angle adjustment value Jh corresponding to the center point spacing difference B2 in the x-axis direction; S33: Determine the positive and negative signs of the longitudinal tilt angle adjustment value Jz according to the comparison result of the magnitudes of Dy1 and Dy2. When Dy1 is greater than Dy2, the longitudinal tilt angle adjustment value Jz is negative, that is, reduce the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z axis in the space coordinate system. When Dy1 is less than Dy2, the longitudinal tilt angle adjustment value Jz is positive, that is, increase the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z axis in the space coordinate system; At the same time, determine the positive and negative signs of the horizontal tilt angle adjustment value Jh according to the comparison result of the magnitudes of Dx1 and Dx2. When Dx1 is less than Dx2, the horizontal tilt angle adjustment value Jh is negative, that is, reduce the angle between the horizontal center line of the front end face of the photovoltaic panel and the positive direction of the X axis in the space coordinate system. When Dy1 is greater than Dy2, the horizontal tilt angle adjustment value Jh is positive, that is, increase the angle between the horizontal center line of the front end face of the photovoltaic panel and the positive direction of the x axis in the space coordinate system; When Dy1 is equal to Dy2, the longitudinal tilt angle adjustment value Jz is zero, and when Dy1 is equal to Dy2, the horizontal tilt angle adjustment value Jh is zero, and no adjustment is performed; S34: Send the longitudinal tilt angle adjustment value Jz and the transverse tilt angle adjustment value Jh including positive and negative attributes to the longitudinal tilt angle adjustment component and the transverse tilt angle adjustment component to adjust the longitudinal tilt angle and the transverse tilt angle of the photovoltaic panel, so as to make the photovoltaic panel face the sun directly.

8. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 7, wherein In the step S32, the correspondence between the center point spacing difference in the y-axis direction and the longitudinal tilt angle adjustment value is stored in the y-axis direction center point spacing difference - longitudinal tilt angle adjustment value database; the correspondence between the center point spacing difference in the x-axis direction and the transverse tilt angle adjustment value is stored in the x-axis direction center point spacing difference - transverse tilt angle adjustment value database.

9. The artificial intelligence system based on panoramic intelligent energy cloud-edge collaboration according to claim 7, wherein In the step S4, the longitudinal tilt angle of the photovoltaic panel refers to the angle between the longitudinal center line of the front end face of the photovoltaic panel and the positive direction of the Z axis in the space coordinate system, and the transverse tilt angle of the photovoltaic panel refers to the angle between the transverse center line of the front end face of the photovoltaic panel and the positive direction of the X axis in the space coordinate system; among them, the X axis and the Y axis in the space coordinate system are located on the ground, the Z axis is vertically upward, and the three axes are perpendicular to each other.

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