Method for treating accumulated dust of photovoltaic power station

Abstract

The invention discloses a photovoltaic power station accumulated dust processing method, which comprises the following steps of performing real-time processing on an acquired infrared image, and acquiring an accumulated dust image on the surface of a photovoltaic panel through an optical imaging module carried on an OpenMV platform; carrying out image preprocessing on the dust deposition image, carrying out edge detection on the preprocessed image by adopting an edge detection algorithm based on morphological gradient, and determining the contour of the sediment to detect the distribution of the sediment; the processed image is transmitted to the APP of the mobile phone end through the WIFI module, so that the working state and the dust accumulation condition of the photovoltaic panel can be checked in real time; the connected dust removal equipment is remotely controlled through the mobile phone terminal APP, and fixed-point dust removal treatment is carried out on the specified photovoltaic module; the dust accumulation condition on the surface of the photovoltaic panel is monitored in real time, fixed-point dust removal treatment is carried out in time, shielding of particles such as dust and sand on the illumination receiving capacity of the surface of the photovoltaic panel is effectively reduced, and therefore the power generation efficiency of a photovoltaic power station is improved.

Description

Technical Field

[0001] The invention relates to a method for treating dust accumulation in a photovoltaic power station. Background Art

[0002] Photovoltaic power generation, as a clean and renewable energy form, has been widely used in the region. Due to its unique geographical environment and climatic conditions, the region provides abundant solar energy resources for photovoltaic power generation. However, these regions also face severe natural environmental challenges, such as strong winds, sandstorms, strong ultraviolet radiation, etc. These factors have a significant impact on the operating efficiency and stability of photovoltaic power stations.

[0003] During the long-term operation of photovoltaic power stations, dust, sand and other particles are easily accumulated on the surface of photovoltaic panels. These deposits not only block the surface of photovoltaic panels and reduce the amount of incident sunlight, but may also cause the temperature of photovoltaic panels to rise, further affecting the power generation efficiency. Especially in the region, due to the dry climate and strong winds and sand, the dust accumulation problem on the surface of photovoltaic panels is more prominent. Therefore, how to effectively deal with the dust accumulation on photovoltaic panels has become a key issue to ensure the efficient and stable operation of photovoltaic power stations.

[0004] Traditional methods of dealing with dust accumulation on photovoltaic panels mostly rely on manual cleaning, which is not only labor-intensive and inefficient, but also difficult to achieve full coverage and timely cleaning of all photovoltaic panels. Summary of the invention

[0005] The purpose of the present invention is to provide a method for treating dust accumulation in a photovoltaic power station to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for treating dust accumulation in a photovoltaic power station, comprising the following steps: Use the infrared thermal imaging module on the OpenMV platform to collect infrared images of photovoltaic panels; Process the collected infrared images in real time to obtain the temperature distribution image of the photovoltaic panel and mark the temperature abnormality areas; The dust accumulation image on the surface of the photovoltaic panel is collected by the optical imaging module mounted on the OpenMV platform; Perform image preprocessing on dust accumulation images, including grayscale, enhancement, binarization, filtering and distortion correction; The edge detection algorithm based on morphological gradient is used to detect the edge of the preprocessed image to determine the outline of the sediment and detect the sediment distribution; The processed images are transmitted to the mobile phone APP through the WIFI module, so that the working status and dust accumulation of the photovoltaic panels can be checked in real time; When a large area of ​​dust accumulation or abnormal temperature area is detected on the surface of the photovoltaic panel, the connected dust removal equipment can be remotely controlled through the mobile phone APP to perform targeted dust removal on the designated photovoltaic components.

[0007] Furthermore, the processing of the infrared image comprises the following steps: Set a specific temperature value range; Collect infrared thermal imaging images; Calculate the color block temperature; Detect whether the target temperature is within the set threshold range. If so, mark the specific temperature area and output the image.

[0008] Furthermore, the image enhancement in the image preprocessing adopts a linear transformation method to transform the grayscale value of the photovoltaic panel image, so that the light and dark contrast of the image is more obvious and the contrast is enhanced; Image binarization uses a global fixed threshold algorithm or an adaptive threshold algorithm to divide the grayscale information in the image into two parts. All pixel values ​​within the threshold range become white, and all pixel values ​​outside the threshold range become black. Image filtering uses a median filter algorithm to process the binarized image to filter out noise; Image distortion correction includes rotation correction and distortion correction. By establishing a functional relationship to perform coordinate correction, an orthographic image is obtained, and the barrel distortion caused by the wide-angle lens is corrected to obtain a smooth distortion-corrected image that conforms to visual characteristics.

[0009] Furthermore, a detection platform based on MATLAB is included, which is used to process the collected original images more carefully and accurately, including: Design a special GUI interface, use MATLAB to package the image processing algorithm needed for detection, and only output the image results, making the display of the detection results more concise and intuitive; Read images, process images, and display the amount of dust accumulation through the GUI interface to calculate the shielding area of ​​the deposits on the photovoltaic panel surface; Connect with the decision-making system and dust removal equipment to provide timely feedback on abnormalities or decision-making options and control the operation of the dust removal equipment.

[0010] Furthermore, the dust removal equipment includes a dust removal robot, which can automatically navigate to the designated photovoltaic module location and perform precise dust removal operations according to instructions issued by a mobile phone APP or a MATLAB detection platform.

[0011] Furthermore, the dust removal equipment also includes an automatic identification and positioning system, which can automatically identify the specific location of the photovoltaic module and confirm its dust accumulation state, so as to quickly and accurately perform dust removal operations when receiving dust removal instructions. Furthermore, it also includes the function of fine-tuning the photovoltaic panel images using the detection platform built on the MATLAB platform. The platform realizes image reading, processing and result display through a graphical user interface. It can intuitively display the dust accumulation on the surface of the photovoltaic panel and calculate the proportion of the dust blocking the photovoltaic panel's light receiving capacity.

[0012] Furthermore, the MATLAB detection platform provides a user interaction function through a GUI interface, allowing the user to directly trigger a dust removal instruction according to the processed image results, and control the connected dust removal equipment to perform automatic or manual dust removal operations.

[0013] Furthermore, the method also includes an intelligent management system, which integrates photovoltaic panel status monitoring, dust accumulation detection, dust removal control and data processing functions, can monitor the operating status of the photovoltaic power station in real time, intelligently analyze the dust accumulation situation, and automatically dispatch dust removal equipment for maintenance, so as to improve the power generation efficiency and operation stability of the photovoltaic power station.

[0014] Compared with the prior art, the present invention has the following beneficial effects: By real-time monitoring of dust accumulation on the surface of photovoltaic panels and timely dust removal at designated locations, the ability of photovoltaic panels to receive light due to dust, sand and other particles is effectively reduced, thereby improving the power generation efficiency of photovoltaic power stations. Compared with the traditional manual cleaning method, the automated and intelligent dust treatment method greatly reduces the labor cost and labor intensity; at the same time, through precise fixed-point dust removal, unnecessary cleaning work is reduced, further reducing maintenance costs; Real-time monitoring of the temperature distribution of photovoltaic panels and marking of abnormal temperature areas help to promptly detect potential hot spot effects and other problems, thereby avoiding damage to photovoltaic panels or reduced power generation efficiency due to excessive temperature, and improving the operational stability of photovoltaic power stations; Through the integrated intelligent management system, the operating status of the photovoltaic power station can be monitored in real time, the dust accumulation situation can be intelligently analyzed, and the dust removal equipment can be automatically dispatched for maintenance; this provides users with rich decision-making support information, making the management of photovoltaic power stations more scientific and efficient; The region has rich solar energy resources. By effectively dealing with the problem of dust accumulation on photovoltaic panels, we can give full play to the energy advantages of these regions and promote the widespread application and sustainable development of renewable energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of a conventional dust removal robot of the present invention; DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Specific implementation method 1, see Figure 1 The present invention provides a technical solution: a method for treating dust accumulation in a photovoltaic power station, comprising the following steps: Use the infrared thermal imaging module on the OpenMV platform to collect infrared images of photovoltaic panels; Process the collected infrared images in real time to obtain the temperature distribution image of the photovoltaic panel and mark the temperature abnormality areas; The dust accumulation image on the surface of the photovoltaic panel is collected by the optical imaging module mounted on the OpenMV platform; Perform image preprocessing on dust accumulation images, including grayscale, enhancement, binarization, filtering and distortion correction; The edge detection algorithm based on morphological gradient is used to detect the edge of the preprocessed image to determine the outline of the sediment and detect the sediment distribution; The processed images are transmitted to the mobile phone APP through the WIFI module, so that the working status and dust accumulation of the photovoltaic panels can be checked in real time; When a large area of ​​dust accumulation or abnormal temperature area is detected on the surface of the photovoltaic panel, the connected dust removal equipment can be remotely controlled through the mobile phone APP to perform targeted dust removal on the designated photovoltaic components.

[0018] The processing of infrared images includes the following steps: Set a specific temperature value range; Collect infrared thermal imaging images; Calculate the color block temperature; Detect whether the target temperature is within the set threshold range. If so, mark the specific temperature area and output the image.

[0019] Infrared image processing code function process_infrared_image(image): temperature_threshold_min = 20 temperature_threshold_max = 80 temperatures = calculate_temperatures(image) marked_image = create_empty_image_like(image) for each pixel in image: temperature = temperatures[pixel.position] if temperature_threshold_min<= temperature<= temperature_threshold_max: marked_image[pixel.position] = [255, 0, 0] return marked_image

[0020] Image enhancement in image preprocessing uses linear transformation method to transform the gray value of photovoltaic panel images, making the light and dark contrast of the image more obvious and enhancing the contrast; Grayscale processing code function grayscale_image(image): # Weighted average parameters R_weight = 0.299 G_weight = 0.587 B_weight = 0.114 gray_image = create_empty_gray_image(image.size) for each pixel in image: R, G, B = pixel.color gray_value = R_weight * R + G_weight * G + B_weight * B gray_image[pixel.position] = gray_value return gray_image Image enhancement processing code import cv2 import numpy as np def linear_transform(image, alpha=1.0, beta=0): """ Perform a linear transformation on the image, the formula is: s = alpha * r + beta Here, s and r represent the output and input pixel values ​​respectively, and alpha and beta are the parameters of the linear transformation.

[0021] """ image_float = image.astype(float) transformed_image = cv2.convertScaleAbs(image_float, alpha=alpha,beta=beta) return transformed_image image = cv2.imread('path_to_image.jpg', cv2.IMREAD_GRAYSCALE) enhanced_image = linear_transform(image, alpha=1.2, beta=30)

[0022] Image binarization uses a global fixed threshold algorithm or an adaptive threshold algorithm to divide the grayscale information in the image into two parts. All pixel values ​​within the threshold range become white, and all pixel values ​​outside the threshold range become black. Image binarization (local fixed threshold algorithm) def binarize_image_global_threshold(image, threshold): binarized_image = create_empty_image_like(image) for pixel in image: if pixel.gray_value>threshold: binarized_image[pixel.position] = 255 else: binarized_image[pixel.position] = 0 return binarized_image ; Binarization (adaptive threshold algorithm) def binarize_image_adaptive_threshold(image, window_size, offset): """ Perform adaptive threshold binarization on the image.

[0023] parameter: - image: input grayscale image - window_size: the size of the local window - offset: the offset to subtract from the local mean return: - binarized_image: binarized image """ binarized_image = create_empty_image_like(image) for x, y in image.positions: window = extract_window(image, (x, y), window_size) local_avg = calculate_average(window) threshold = local_avg - offset if image[x, y].gray_value>threshold: binarized_image[x, y] = 255 else: binarized_image[x, y] = 0 return binarized_image

[0024] Image filtering uses a median filter algorithm to process the binarized image to filter out noise; Filtering (Median filter algorithm) def median_filter_image(image, kernel_size): """ Perform median filtering on the image.

[0025] parameter: - image: input grayscale image - kernel_size: kernel size of median filter (odd number) return: - filtered_image: filtered image """ filtered_image = create_empty_image_like(image) for x, y in image.positions: window = extract_window(image, (x, y), kernel_size) pixel_values ​​= [pixel.gray_value for pixel in window] median_value = median(pixel_values) filtered_image[x, y] = median_value return filtered_image ; Image distortion correction includes rotation correction and distortion correction. By establishing a functional relationship to perform coordinate correction, an orthographic image is obtained, and the barrel distortion caused by the wide-angle lens is corrected to obtain a smooth distortion-corrected image that conforms to visual characteristics.

[0026] import cv2 import numpy as np def undistort_and_rotate_image(img, camera_matrix, dist_coeffs,rotation_matrix, translation_vector): h, w = img.shape[:2] newcameramtx, roi = cv2.getOptimalNewCameraMatrix(camera_matrix,dist_coeffs, (w,h), 1, (w,h)) dst = cv2.undistort(img, camera_matrix, dist_coeffs, None,newcameramtx) x, y, w, h = roi dst = dst[y:y+h, x:x+w] return dst img = cv2.imread('path_to_your_image.jpg') corrected_img = undistort_and_rotate_image(img, camera_matrix, dist_coeffs, None, None) cv2.imshow('Corrected Image', corrected_img) cv2.waitKey(0) cv2.destroyAllWindows() It also includes a MATLAB-based detection platform, which is used to process the collected raw images more carefully and accurately, including: Design a special GUI interface, use MATLAB to package the image processing algorithm needed for detection, and only output the image results, making the display of the detection results more concise and intuitive; Read images, process images, and display the amount of dust accumulation through the GUI interface to calculate the shielding area of ​​the deposits on the photovoltaic panel surface; Connect with the decision-making system and dust removal equipment to provide timely feedback on abnormalities or decision-making options and control the operation of the dust removal equipment.

[0027] MATLAB detection platform algorithm function detection_platform_gui hFig = figure('Name', 'Photovoltaic panel dust detection platform'); hAxes = axes('Parent', hFig); while ishandle(hFig) if new_image_available img = read_new_image(); processed_img = process_image(img); imshow(processed_img, 'Parent', hAxes); if needs_cleaning(processed_img) send_cleaning_command_to_device(); end end end end function processed_img = process_image(img) end function send_cleaning_command_to_device() end In practical applications, write and adjust the corresponding MATLAB code according to specific needs and environment The dust removal equipment includes a dust removal robot, which can automatically navigate to the designated photovoltaic module location and perform precise dust removal operations according to instructions issued by the mobile phone APP or MATLAB detection platform.

[0028] The dust removal equipment also includes an automatic identification and positioning system that can automatically identify the specific location of the photovoltaic module and confirm its dust accumulation status, so that dust removal operations can be carried out quickly and accurately when dust removal instructions are received. It also includes the function of fine-tuning the photovoltaic panel images using the detection platform built on the MATLAB platform. The platform realizes image reading, processing and result display through a graphical user interface. It can intuitively display the dust accumulation on the surface of the photovoltaic panel and calculate the proportion of the area blocked by dust accumulation to the photovoltaic panel's light receiving capacity.

[0029] The MATLAB detection platform provides user interaction functions through the GUI interface, allowing users to directly trigger dust removal instructions based on the processed image results and control the connected dust removal equipment to perform automatic or manual dust removal operations.

[0030] The method also includes an intelligent management system that integrates photovoltaic panel status monitoring, dust accumulation detection, dust removal control and data processing functions. The system can monitor the operating status of the photovoltaic power station in real time, intelligently analyze the dust accumulation situation, and automatically schedule dust removal equipment for maintenance to improve the power generation efficiency and operation stability of the photovoltaic power station.

[0031] After the infrared image and dust accumulation image are collected, the image fusion technology is introduced to fuse the two at the pixel level or feature level. Through the fusion process, the temperature distribution and dust accumulation of the photovoltaic panel can be displayed at the same time, providing more comprehensive information for subsequent dust accumulation analysis and dust removal decisions. The multi-source image fusion algorithm is used to accurately match the temperature abnormality area in the infrared image with the high dust accumulation area in the dust accumulation image, marking the area with both temperature abnormality and high dust accumulation as the priority dust removal target. Add a dust accumulation level assessment system to automatically classify and grade the pre-processed dust accumulation images; the system can classify the dust accumulation level into light, medium and heavy levels based on the distribution, density and thickness of the dust accumulation; different levels of dust accumulation will correspond to different dust removal strategies and maintenance cycles, thereby achieving more accurate and efficient dust accumulation management; A dynamic threshold adjustment strategy is introduced for steps such as binarization and edge detection in image processing. Since factors such as lighting conditions and weather changes can affect the quality of image acquisition, fixed threshold settings may not be suitable for all situations. By monitoring image quality parameters in real time, the thresholds of binarization and edge detection are dynamically adjusted to ensure accurate image processing results in various environments. Integrate more advanced scheduling algorithms in the intelligent management system to realize intelligent scheduling of dust removal equipment; dynamically plan the priority and execution order of dust removal tasks based on the dust accumulation level of photovoltaic panels, the decline in power generation efficiency, and the working status of dust removal equipment; at the same time, optimize the path planning of dust removal equipment in combination with the geographical location, layout, and equipment distribution of photovoltaic power stations, reduce movement time and energy consumption, and improve dust removal efficiency; The interactive interface between the mobile APP and the MATLAB detection platform is optimized to make it more user-friendly and intuitive. More visual elements and interactive controls are added to the APP to enable users to easily view the status of the photovoltaic panels, dust accumulation, and dust removal progress. At the same time, detailed operation guides and help documents are provided to help users quickly get started and make full use of these tools for remote monitoring and maintenance management of photovoltaic power plants. A cloud-edge collaborative data processing architecture is adopted to shift some data processing tasks from the cloud to edge devices. Edge computing is used to reduce data transmission delays and bandwidth consumption, and improve the real-time and reliability of data processing. At the same time, the powerful computing power and massive storage resources of the cloud are used to further analyze and mine the data uploaded by edge devices, providing more in-depth and comprehensive support for the long-term operation and optimization of photovoltaic power stations.

[0032] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for treating dust accumulation in a photovoltaic power station, characterized in that: The following steps are involved: Use the infrared thermal imaging module on the OpenMV platform to collect infrared images of photovoltaic panels; Process the collected infrared images in real time to obtain the temperature distribution image of the photovoltaic panel and mark the temperature abnormality areas; The dust accumulation image on the surface of the photovoltaic panel is collected by the optical imaging module mounted on the OpenMV platform; Perform image preprocessing on dust accumulation images, including grayscale, enhancement, binarization, filtering and distortion correction; The edge detection algorithm based on morphological gradient is used to detect the edge of the preprocessed image to determine the outline of the sediment and detect the sediment distribution; The processed images are transmitted to the mobile phone APP through the WIFI module, so that the working status and dust accumulation of the photovoltaic panels can be checked in real time; When a large area of ​​dust accumulation or abnormal temperature area is detected on the surface of the photovoltaic panel, the connected dust removal equipment can be remotely controlled through the mobile phone APP to perform targeted dust removal on the designated photovoltaic components.

2. A method for treating dust accumulation in a photovoltaic power station according to claim 1, characterized in that: The processing of the infrared image comprises the following steps: Set a specific temperature value range; Collect infrared thermal imaging images; Calculate the color block temperature; Detect whether the target temperature is within the set threshold range. If so, mark the specific temperature area and output the image.

3. A method for treating dust accumulation in a photovoltaic power station according to claim 1, characterized in that: The image enhancement in the image preprocessing adopts a linear transformation method to transform the grayscale value of the photovoltaic panel image, so that the light and dark contrast of the image is more obvious and the contrast is enhanced; Image binarization uses a global fixed threshold algorithm or an adaptive threshold algorithm to divide the grayscale information in the image into two parts. All pixel values ​​within the threshold range become white, and all pixel values ​​outside the threshold range become black. Image filtering uses a median filter algorithm to process the binarized image to filter out noise; Image distortion correction includes rotation correction and distortion correction. By establishing a functional relationship to perform coordinate correction, an orthographic image is obtained, and the barrel distortion caused by the wide-angle lens is corrected to obtain a smooth distortion-corrected image that conforms to visual characteristics.

4. A method for treating dust accumulation in a photovoltaic power station according to claim 1, characterized in that: It also includes a MATLAB-based detection platform, which is used to process the collected raw images more carefully and accurately, including: Design a special GUI interface, use MATLAB to package the image processing algorithm needed for detection, and only output the image results, making the display of the detection results more concise and intuitive; Read images, process images, and display the amount of dust accumulation through the GUI interface to calculate the shielding area of ​​the deposits on the photovoltaic panel surface; Connect with the decision-making system and dust removal equipment to provide timely feedback on abnormalities or decision-making options and control the operation of the dust removal equipment.

5. A method for treating dust accumulation in a photovoltaic power station according to claim 1, characterized in that: The dust removal equipment includes a dust removal robot, which can automatically navigate to the designated photovoltaic module location and perform precise dust removal operations according to instructions issued by a mobile phone APP or a MATLAB detection platform.

6. A method for treating dust accumulation in a photovoltaic power station according to claim 5, characterized in that: The dust removal equipment also includes an automatic identification and positioning system, which can automatically identify the specific location of the photovoltaic component and confirm its dust accumulation status, so that dust removal operations can be performed quickly and accurately when a dust removal instruction is received.

7. A method for treating dust accumulation in a photovoltaic power station according to claim 1, characterized in that: It also includes the function of fine-tuning the photovoltaic panel images using the detection platform built on the MATLAB platform. The platform realizes image reading, processing and result display through a graphical user interface. It can intuitively display the dust accumulation on the surface of the photovoltaic panel and calculate the proportion of the area blocked by dust accumulation to the photovoltaic panel's light receiving capacity.

8. A method for treating dust accumulation in a photovoltaic power station according to claim 1, characterized in that: The MATLAB detection platform provides a user interaction function through a GUI interface, allowing the user to directly trigger a dust removal instruction according to the processed image results, and control the connected dust removal equipment to perform automatic or manual dust removal operations.

9. A method for treating dust in a photovoltaic power station according to any one of claims 1 to 8, characterized in that: The method also includes an intelligent management system that integrates photovoltaic panel status monitoring, dust accumulation detection, dust removal control and data processing functions. The system can monitor the operating status of the photovoltaic power station in real time, intelligently analyze the dust accumulation situation, and automatically schedule dust removal equipment for maintenance to improve the power generation efficiency and operation stability of the photovoltaic power station.

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