WO2024021548A1 - Photovoltaic power generation intelligent operation and maintenance method and system, and storage medium - Google Patents

Photovoltaic power generation intelligent operation and maintenance method and system, and storage medium Download PDF

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WO2024021548A1
WO2024021548A1 PCT/CN2023/073799 CN2023073799W WO2024021548A1 WO 2024021548 A1 WO2024021548 A1 WO 2024021548A1 CN 2023073799 W CN2023073799 W CN 2023073799W WO 2024021548 A1 WO2024021548 A1 WO 2024021548A1
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power generation
photovoltaic
photovoltaic power
image information
status
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PCT/CN2023/073799
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French (fr)
Chinese (zh)
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吴跃波
朱征勇
黄绍宽
陈娅
罗友珍
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重庆跃达新能源有限公司
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Publication of WO2024021548A1 publication Critical patent/WO2024021548A1/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management
    • G06Q10/103—Workflow collaboration or project management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/20—Administration of product repair or maintenance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Energy or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/40—Extraction of image or video features
    • G06V10/44—Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
    • G06V10/761—Proximity, similarity or dissimilarity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/77—Processing image or video features in feature spaces; using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]; Blind source separation
    • G06V10/80—Fusion, i.e. combining data from various sources at the sensor level, preprocessing level, feature extraction level or classification level
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/17—Terrestrial scenes taken from planes or by drones
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/50—Photovoltaic [PV] energy

Definitions

  • the present invention relates to the technical field of photovoltaic power generation, and specifically to photovoltaic power generation intelligent operation and maintenance methods, systems and storage media.
  • a photovoltaic power station refers to a photovoltaic power generation system that uses solar energy and uses special materials such as crystalline silicon panels, inverters and other electronic components. It is connected to the power grid and delivers power to the grid. Because solar energy has inexhaustible and With the advantages of being inexhaustible, safe and reliable, and not polluting the environment or destroying the ecological balance, it is regarded as one of the renewable energy sources with the best development prospects. With the continuous increase of photovoltaic power stations, the operation and maintenance work of photovoltaic power stations is becoming more and more important. Be taken seriously. In actual operation, the shielding of dust and other debris will reduce the absorption of solar radiation by the module, affect the surface heat dissipation of the module, and reduce the photoelectric conversion efficiency.
  • the photovoltaic power generation system needs to be operated and maintained (referred to as operation and maintenance).
  • operation and maintenance The current operation and maintenance method of photovoltaic power stations still relies on manual work, relying on staff to use scanners to inspect hot spots and use artificial naked eye observation to detect dust.
  • Most photovoltaic power plants are built in harsh environments such as the wild or deserts. It is usually difficult for workers to reach the operating area, which brings a lot of inconvenience to troubleshooting and processing during the operation and maintenance process. At the same time, it is also time-consuming to rely on manual troubleshooting for large photovoltaic power plants. laborious and less efficient problem.
  • the present invention is intended to provide an intelligent operation and maintenance method for photovoltaic power generation. It identifies photovoltaic components and their status through images, and generates corresponding maintenance plans based on the status of the photovoltaic components. It can save a lot of manpower and effectively improve the troubleshooting and processing of photovoltaic power generation operation and maintenance. s efficiency.
  • the technical solution provided by the invention is: a photovoltaic power generation intelligent operation and maintenance method, which includes the following steps:
  • S1 Collect image information of the photovoltaic power generation area
  • S4 Generate maintenance plans based on the status of photovoltaic components.
  • the working principle and advantage of the present invention are that the method of the present invention mainly uses image recognition to troubleshoot problems and generate solutions.
  • image information of the photovoltaic power generation area is collected. This process replaces the steps of manual inspection and naked eye observation. Then the collected images are analyzed to identify the specific information of the photovoltaic components, including type, model, connection relationship and other information.
  • the method of the present invention analyzes the current operating status of the photovoltaic component through historical image information. Finally, the corresponding maintenance plan is generated based on the current operating status. At this point, the staff can know the current problems of the photovoltaic power station, the operating status, and the corresponding maintenance plan.
  • the above plan eliminates the need for manual inspection by staff and can save money. A large number of manpower can effectively improve the efficiency of troubleshooting and processing during photovoltaic power generation operation and maintenance.
  • the S1 includes:
  • S1-2 Analyze power generation data and identify photovoltaic power generation areas with abnormal power generation
  • S1-3 Collect image information of photovoltaic power generation areas with abnormal power generation.
  • the current photovoltaic power stations occupy an increasingly larger area, and there is also a large workload for image recognition of the entire station.
  • the photovoltaic power generation data analysis is first improved before image recognition to narrow down the troubleshooting. scope. Taking the area as a unit, the recent power generation data is analyzed and compared with the past power generation data. Based on the attenuation ratio of the power generation, it is judged whether the power generation of the photovoltaic power generation area is abnormal, and then the next step of image recognition of the abnormal power generation area is carried out. The above method is helpful to improve the efficiency of troubleshooting.
  • image information of the photovoltaic power generation area is collected through a drone or a surveillance camera, and the image information includes visible light images and infrared images.
  • the image information collected includes visible light images and infrared images. Visible light images can troubleshoot the appearance and color of photovoltaic components. Infrared images can identify photovoltaic illumination on photovoltaic panels and other components, and determine whether there are hot spots through abnormal photovoltaic illumination. phenomenon and discover problems that are difficult to observe with the naked eye.
  • the S2 includes:
  • S2-1 Perform a clearing process on the image information.
  • the clearing process is to analyze the image frame by frame and select the best color difference.
  • Several small images through the image multi-frame fusion algorithm, generate an image with stable ambient light and enhance the contrast and color of the image;
  • S2-2 Analyze the sharpened image information and identify photovoltaic components.
  • the collected image information is processed to clarify it to facilitate the subsequent identification process.
  • the S2-2 includes:
  • S2-2-1 Analyze the sharpened image information and obtain the target outline
  • S2-2-2 Compare the target outline with the component model library to identify specific photovoltaic components.
  • the specific information such as the model of the photovoltaic component is determined through the contour recognition method. After obtaining the specific photovoltaic component, targeted inspection can be carried out, which is conducive to rapid troubleshooting of problems.
  • the S3 includes:
  • S3-1 According to the photovoltaic component, obtain several inspection items of the photovoltaic component;
  • S3-2 Analyze the status of each inspection item of the photovoltaic component based on historical image information.
  • the current status of each inspection item can be determined based on comparative analysis of the before and after images.
  • the above method can quickly identify external problems of photovoltaic components and is suitable for a wide range of inspections of large photovoltaic stations.
  • image recognition a more comprehensive external inspection of photovoltaic components can be carried out, which is subdivided into aspects such as shape integrity, covering, photovoltaic illumination and nearby debris.
  • the algorithm based on the contour recognition and color recognition of visible light images can analyze and identify the percentage of shape integrity of the photovoltaic component, that is, whether there are defects, deformations, rusts, etc.
  • the real-time photovoltaic illumination of photovoltaic components can be identified through infrared images. According to the difference before and after the photovoltaic illumination images, the hot spots and hot spot locations on the photovoltaic components can be identified.
  • the S4 includes:
  • S4-1 Generate several maintenance plans based on the status of photovoltaic components
  • S4-2 Obtain the lighting conditions and select a maintenance plan based on the lighting conditions.
  • each inspection item of photovoltaic components According to the status of each inspection item of photovoltaic components, multiple corresponding maintenance plans are generated, and then specific maintenance plans are selected according to the lighting conditions to avoid affecting the power generation efficiency of the photovoltaic power station during the maintenance process and avoiding additional economic losses.
  • the S3 also includes:
  • S3-3 Calculate the predicted power generation loss of photovoltaic components based on the status of each inspection item
  • S3-4 Compare the predicted power generation loss with the actual power generation loss, and analyze the causes of power generation loss
  • the causes of power generation loss include external causes and internal causes, and the status of the photovoltaic component includes external status and internal status.
  • the specific internal causes need to be analyzed. Based on the internal and external reasons, the external and internal states of the photovoltaic components are analyzed and the internal and external states of the photovoltaic components are counted to facilitate the subsequent steps to generate corresponding maintenance plans for the internal and external states of the photovoltaic components.
  • the present invention also provides a photovoltaic power generation intelligent operation and maintenance system, which adopts the above-mentioned photovoltaic power generation intelligent operation and maintenance method.
  • the present invention also provides a computer-readable storage medium.
  • a computer program is stored on the storage medium.
  • the computer program is executed by a processor, the above-mentioned intelligent operation and maintenance method for photovoltaic power generation is implemented.
  • Figure 1 is a logical block diagram of the intelligent operation and maintenance method of photovoltaic power generation according to an embodiment of the present invention.
  • this embodiment discloses a photovoltaic power generation intelligent operation and maintenance method, which specifically includes the following steps (the numbers of each step in this solution are only used to distinguish the steps and do not limit the specific execution order of each step, and each step also Can be performed simultaneously):
  • S1-1 Obtain photovoltaic power generation data. Obtain the recent power generation data of the photovoltaic power station.
  • S1-2 Analyze the power generation data and identify photovoltaic power generation areas with abnormal power generation. Taking the area as a unit, the recent power generation data is analyzed and compared with the past power generation data, and based on the attenuation ratio of the power generation, it is judged whether the power generation of the photovoltaic power generation area is abnormal.
  • S1-3 Collect image information of photovoltaic power generation areas with abnormal power generation. After determining the photovoltaic power generation area with abnormal power generation, collect images of the photovoltaic power generation area through the dynamic camera of the drone or the fixed surveillance camera of the photovoltaic power generation area.
  • the cameras for image collection include visible light cameras and infrared cameras, which can Visible light images and infrared images are collected separately.
  • the images collected in this embodiment are mainly outdoor photovoltaic panels and other components.
  • S2-1 Perform a clearing process on the image information.
  • the clearing process is to analyze the image frame by frame, select several images with the smallest color difference, and use a multi-frame image fusion algorithm to generate an image with stable ambient light and enhance the image quality. Contrast and color.
  • the initially collected images are usually blurry and lack clarity, which affects the next step of analysis and identification.
  • This embodiment mainly aims at the problem of unclear collected images caused by flickering of ambient light at the photovoltaic power generation site.
  • the collected image information is analyzed, several images with the smallest color difference are selected, and the multi-frame image fusion algorithm is used to correspond to the multi-frame images at different times.
  • the gray values of the pixels are added together to obtain their time-average image.
  • S2-2-1 Analyze the sharpened image information and obtain the target contour.
  • the processed image information is processed layer by layer to obtain the target contour curve in the image.
  • S2-2-2 Compare the target outline with the component model library to identify specific photovoltaic components. Compare the target contour curve with the model component library of the database, and identify the specific model of the photovoltaic equipment there, such as photovoltaic panels, combiner boxes, inverters and other components through image similarity matching and BP neural network algorithms.
  • S3-1 According to the photovoltaic component, obtain several inspection items of the photovoltaic component.
  • the specific photovoltaic component is identified, and the main inspection items of the photovoltaic component are obtained according to the operation and maintenance procedures of the specific model of the photovoltaic component, and organized into a list of inspection items.
  • the main inspection items include the appearance integrity and covering of the photovoltaic component. , photovoltaic illumination and nearby debris. For example, if the identified photovoltaic component is a photovoltaic panel, the shape, coverage, and Further inspections will be conducted on items such as objects and photovoltaic illumination.
  • S3-2 Analyze the status of each inspection item of the photovoltaic component based on historical image information.
  • the above inspection items mainly obtain the historical image information of the photovoltaic component, and judge the current status of each inspection item based on the comparative analysis of the before and after images.
  • the photovoltaic panel is used as the inspection object.
  • the algorithm of contour recognition and color recognition of the visible light image can analyze and identify the shape integrity percentage of the photovoltaic component, that is, whether there are defects, deformations, rusts, etc. in the shape; the coverage of the photovoltaic component
  • the condition of objects that is, the coverage and proportion of foreign objects such as dust, bird droppings, leaves, etc.
  • the real-time photovoltaic illumination of the photovoltaic panel can be identified through infrared images. According to the difference before and after the photovoltaic illumination image, the hot spot condition and hot spot location on the photovoltaic panel can be identified.
  • S4-1 Generate several maintenance plans based on the status of photovoltaic components. According to the status of each inspection item of the photovoltaic components, multiple corresponding maintenance plans are generated. For example, for the problem of covering on the photovoltaic panels, during the maintenance process, you can choose rag cleaning or flushing cleaning, select the water temperature for flushing and cleaning, etc., specific Plan selection also requires subsequent judgment.
  • S4-2 Obtain the lighting conditions and select a maintenance plan based on the lighting conditions.
  • the illumination conditions obtained in this embodiment include illumination angle and photovoltaic temperature. Choosing specific maintenance plans based on light conditions is mainly to avoid affecting the power generation efficiency of the photovoltaic power station during the maintenance process and avoid causing additional economic losses. For example, in the maintenance plan generated above for the problem of covering on photovoltaic panels, there is a rag cleaning or flushing cleaning plan. First, the current illumination angle is obtained, and the coincidence degree of the illumination angle and the orientation angle of the photovoltaic array is compared. If the coincidence degree is high (difference) value angle within 15 degrees), the current illumination angle is direct light.
  • the illumination angle is direct light Choose flush cleaning, that is, flush with water from a distance to avoid the impact of artificial occlusion on the photovoltaic array. If the overlap between the current illumination angle and the orientation angle of the photovoltaic array is low (the difference angle exceeds 15 degrees), then the current illumination angle is scattered light and the light does not directly illuminate the photovoltaic array. You can use a rag with a more detailed cleaning effect to clean.
  • the cleaning process generally uses clean water and a flexible brush or rag for cleaning.
  • the surface temperature of the photovoltaic array module is higher. Direct contact with cold water may cause damage to the glass or components, so it is also necessary to obtain the surface of the photovoltaic module.
  • Temperature select the appropriate cleaning water temperature according to the photovoltaic surface temperature.
  • the temperature difference between the photovoltaic surface temperature and the cleaning water temperature is no more than 8°C, which can avoid irreversible damage to the photovoltaic panels caused by excessive temperature differences.
  • step S3 also includes the following steps:
  • S3-3 Calculate the predicted power generation loss of photovoltaic components based on the status of each inspection item.
  • the external status of the photovoltaic component is identified from the image analysis, such as the shape integrity of the photovoltaic panel, surface coverage, and surrounding debris.
  • S3-4 Compare the predicted power generation loss with the actual power generation loss, and analyze the causes of power generation loss. Compare and analyze the calculated predicted power generation loss with the actual power generation loss. For example, whether the change pattern of the predicted power generation loss due to photovoltaic panel shading is consistent with the actual power generation loss. If the difference between the two is not large, then the current power generation loss is judged. The amount is caused by external causes. If the difference between the two is large, it is judged that in addition to external causes, there are also internal causes of the photovoltaic components that cause the loss of power generation.
  • S3-5 Analyze the status of photovoltaic components based on the causes of power generation loss.
  • the causes of power generation loss include external causes obtained through image recognition and internal causes obtained through data analysis. Based on both internal and external causes, the external and internal states of the photovoltaic components are analyzed. For example, currently one-half of the external area of photovoltaic panels is blocked, and there are large line losses and aging of photovoltaic panels inside. Statistics of the internal and external status of photovoltaic components will facilitate subsequent steps to generate corresponding maintenance plans based on the internal and external status of photovoltaic components.
  • the method of the present invention not only uses images to identify the external status of photovoltaic components, but also uses this technology to analyze and identify whether there are problems inside the photovoltaic components based on actual power generation data, and further determines the internal status of the photovoltaic components based on historical data analysis. Because this solution can more realistically divide the internal and external problems of photovoltaic components, it can more accurately identify the current status of photovoltaic components.
  • This embodiment also provides a photovoltaic power generation intelligent operation and maintenance system, which adopts the above photovoltaic power generation intelligent operation and maintenance method.
  • This embodiment also provides a computer-readable storage medium.
  • a computer program is stored on the storage medium.
  • the computer program is executed by a processor, the above-mentioned intelligent operation and maintenance method for photovoltaic power generation is implemented.

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Abstract

The present invention relates to the technical field of photovoltaic power generation. Disclosed in the present invention is a photovoltaic power generation intelligent operation and maintenance method, which comprises the following steps: S1, collecting image information of a photovoltaic power generation area; S2, analyzing the image information, and identifying a photovoltaic part; S3, in combination with historical image information, analyzing the state of the photovoltaic part; and S4, generating a maintenance solution according to the state of the photovoltaic part. The present invention identifies a photovoltaic part and the state thereof on the basis of images, and generates a corresponding maintenance solution according to the state of the photovoltaic part, thus saving a large amount of manpower, and effectively increasing the troubleshooting and processing efficiency during photovoltaic power generation operation and maintenance processes.

Description

光伏发电智能运维方法、系统及存储介质Photovoltaic power generation intelligent operation and maintenance methods, systems and storage media 技术领域Technical field
本发明涉及光伏发电技术领域，具体涉及光伏发电智能运维方法、系统及存储介质。The present invention relates to the technical field of photovoltaic power generation, and specifically to photovoltaic power generation intelligent operation and maintenance methods, systems and storage media.
背景技术Background technique
光伏电站，是指一种利用太阳能，采用特殊材料诸如晶硅板、逆变器等电子元件组成的发电体系，与电网相连并向电网输送电力的光伏发电系统，由于太阳能具有取之不尽、用之不竭、安全可靠、不会污染环境和破坏生态平衡等优点，被视为发展前景最好的可再生能源之一，随着光伏电站的持续增加，光伏电站的运维工作越来越受到重视。在实际运行中，灰尘等杂物的遮蔽会降低组件对太阳辐射的吸收，影响组件表面散热，降低光电转换效率，而高于组件的杂草、飞溅的泥浆、鸟粪等都会对组件产生不均匀的局部遮挡，久而久之就会形成热斑，从而不同程度地降低组件的输出功率，严重的可导致电池组件局部烧毁，由于热斑效应引起光伏电站起火的事件时有发生，以上各种环境因素都给光伏电站的安全运行带来了很大的隐患。A photovoltaic power station refers to a photovoltaic power generation system that uses solar energy and uses special materials such as crystalline silicon panels, inverters and other electronic components. It is connected to the power grid and delivers power to the grid. Because solar energy has inexhaustible and With the advantages of being inexhaustible, safe and reliable, and not polluting the environment or destroying the ecological balance, it is regarded as one of the renewable energy sources with the best development prospects. With the continuous increase of photovoltaic power stations, the operation and maintenance work of photovoltaic power stations is becoming more and more important. Be taken seriously. In actual operation, the shielding of dust and other debris will reduce the absorption of solar radiation by the module, affect the surface heat dissipation of the module, and reduce the photoelectric conversion efficiency. Weeds, splashing mud, bird droppings, etc. that are higher than the module will have adverse effects on the module. Uniform partial occlusion will form hot spots over time, thereby reducing the output power of the module to varying degrees. In severe cases, it can cause local burning of the battery module. Fires in photovoltaic power stations occur due to the hot spot effect. Various environmental factors mentioned above All have brought great hidden dangers to the safe operation of photovoltaic power plants.
为了保证整个系统可以安全、稳定的运行，则需要对光伏发电系统进行运行维护(简称运维)。目前的光伏电站运维方式依旧是靠人工开展工作，依靠工作人员采用扫描仪对热斑实施排查，用人工肉眼的观察方式检测灰尘。大多数光伏电站多数建在野外或者荒漠等恶劣环境中，工作人员通常难以到达作业区域，给运维过程的问题排查和处理工作带来诸多不便，同时偌大的光伏电站依靠人工进行排查也存在费时费力且效率较低的问题。In order to ensure that the entire system can operate safely and stably, the photovoltaic power generation system needs to be operated and maintained (referred to as operation and maintenance). The current operation and maintenance method of photovoltaic power stations still relies on manual work, relying on staff to use scanners to inspect hot spots and use artificial naked eye observation to detect dust. Most photovoltaic power plants are built in harsh environments such as the wild or deserts. It is usually difficult for workers to reach the operating area, which brings a lot of inconvenience to troubleshooting and processing during the operation and maintenance process. At the same time, it is also time-consuming to rely on manual troubleshooting for large photovoltaic power plants. laborious and less efficient problem.
发明内容Contents of the invention
本发明意在提供光伏发电智能运维方法，通过图像识别光伏部件及其状态，并根据光伏部件的状态生成相应维护方案，能够节省大量人力，有效提高光伏发电运维过程中的问题排查和处理的效率。The present invention is intended to provide an intelligent operation and maintenance method for photovoltaic power generation. It identifies photovoltaic components and their status through images, and generates corresponding maintenance plans based on the status of the photovoltaic components. It can save a lot of manpower and effectively improve the troubleshooting and processing of photovoltaic power generation operation and maintenance. s efficiency.
本发明提供的技术方案为：光伏发电智能运维方法，包括以下步骤：The technical solution provided by the invention is: a photovoltaic power generation intelligent operation and maintenance method, which includes the following steps:
S1：采集光伏发电区域的图像信息；S1: Collect image information of the photovoltaic power generation area;
S2：分析图像信息，识别光伏部件； S2: Analyze image information and identify photovoltaic components;
S3：结合历史图像信息分析光伏部件的状态；S3: Analyze the status of photovoltaic components based on historical image information;
S4：根据光伏部件的状态生成维护方案。S4: Generate maintenance plans based on the status of photovoltaic components.
本发明的工作原理及优点在于：本发明方法主要通过图像识别方式进行问题排查并生成方案。首先采集光伏发电区域的图像信息，此过程替代了人工巡视和肉眼观察的步骤，然后对采集的图像进行分析，识别出光伏部件的具体信息，包括种类、型号和连接关系等信息。识别出具体的光伏部件后，本发明方法通过历史图像信息，分析该光伏部件目前的运行状态。最后根据当前运行状态生成相应的维护方案，至此工作人员能够得知光伏电站当前所存在的问题，运行的状态，以及相应的维护方案，通过上述方案免去了工作人员人工排查的步骤，能够节省大量人力，有效提高光伏发电运维过程中的问题排查和处理的效率。The working principle and advantage of the present invention are that the method of the present invention mainly uses image recognition to troubleshoot problems and generate solutions. First, image information of the photovoltaic power generation area is collected. This process replaces the steps of manual inspection and naked eye observation. Then the collected images are analyzed to identify the specific information of the photovoltaic components, including type, model, connection relationship and other information. After identifying a specific photovoltaic component, the method of the present invention analyzes the current operating status of the photovoltaic component through historical image information. Finally, the corresponding maintenance plan is generated based on the current operating status. At this point, the staff can know the current problems of the photovoltaic power station, the operating status, and the corresponding maintenance plan. The above plan eliminates the need for manual inspection by staff and can save money. A large number of manpower can effectively improve the efficiency of troubleshooting and processing during photovoltaic power generation operation and maintenance.
进一步，所述S1包括：Further, the S1 includes:
S1-1：获取光伏的发电量数据；S1-1: Obtain photovoltaic power generation data;
S1-2：分析发电量数据，识别发电量异常的光伏发电区域；S1-2: Analyze power generation data and identify photovoltaic power generation areas with abnormal power generation;
S1-3：采集发电量异常的光伏发电区域的图像信息。S1-3: Collect image information of photovoltaic power generation areas with abnormal power generation.
目前的光伏电站占地面积也越来越大，对全站图像识别也存在很大的工作量，为了提高问题排查效率，快速锁定问题，在图像识别前先提高光伏发电量数据分析来缩小排查范围。以区域为单位，将最近的发电量数据与往日发电量数据分析对比，根据发电量的衰减比例，判断该光伏发电区域的发电量是否异常，再对异常发电区域进行下一步的图像识别。通过上述方法有利于提高问题排查效率。The current photovoltaic power stations occupy an increasingly larger area, and there is also a large workload for image recognition of the entire station. In order to improve the efficiency of troubleshooting and quickly locate the problem, the photovoltaic power generation data analysis is first improved before image recognition to narrow down the troubleshooting. scope. Taking the area as a unit, the recent power generation data is analyzed and compared with the past power generation data. Based on the attenuation ratio of the power generation, it is judged whether the power generation of the photovoltaic power generation area is abnormal, and then the next step of image recognition of the abnormal power generation area is carried out. The above method is helpful to improve the efficiency of troubleshooting.
进一步，所述S1中通过无人机或监控摄像头采集光伏发电区域的图像信息，所述图像信息包括可见光图像和红外图像。Further, in S1, image information of the photovoltaic power generation area is collected through a drone or a surveillance camera, and the image information includes visible light images and infrared images.
通过无人机的动态摄像头或该光伏发电区域的固定式监控摄像头，对光伏发电区域的图像进行采集，通过多方面渠道获取图像信息，有利于问题排查过程中图像信息的采集。并且采集的图像信息包括可见光图像和红外图像，可见光图像能够对光伏部件的外形颜色等方面进行问题排查，红外图像则能够识别光伏板等部件上的光伏照度，通过光伏照度异常判断是否有热斑现象，发现肉眼难以观察的问题。Collect images of the photovoltaic power generation area through the dynamic camera of the drone or the fixed surveillance camera in the photovoltaic power generation area, and obtain image information through multiple channels, which is conducive to the collection of image information during the problem troubleshooting process. The image information collected includes visible light images and infrared images. Visible light images can troubleshoot the appearance and color of photovoltaic components. Infrared images can identify photovoltaic illumination on photovoltaic panels and other components, and determine whether there are hot spots through abnormal photovoltaic illumination. phenomenon and discover problems that are difficult to observe with the naked eye.
进一步，所述S2包括：Further, the S2 includes:
S2-1：对图像信息进行清晰化处理，所述清晰化处理为对图像逐帧分析，选取色差最 小的若干张图像，通过图像多帧融合算法，生成环境光稳定的图像，并增强图像的对比度和色彩；S2-1: Perform a clearing process on the image information. The clearing process is to analyze the image frame by frame and select the best color difference. Several small images, through the image multi-frame fusion algorithm, generate an image with stable ambient light and enhance the contrast and color of the image;
S2-2：分析清晰化处理后的图像信息，识别光伏部件。S2-2: Analyze the sharpened image information and identify photovoltaic components.
针对光伏发电现场环境光闪烁等因素导致采集的图像不清晰的问题，对采集的图像信息进行清晰化处理，便于后续的识别过程。In order to solve the problem of unclear collected images caused by factors such as ambient light flickering at the photovoltaic power generation site, the collected image information is processed to clarify it to facilitate the subsequent identification process.
进一步，所述S2-2包括：Further, the S2-2 includes:
S2-2-1：分析清晰化处理后的图像信息，获取目标轮廓；S2-2-1: Analyze the sharpened image information and obtain the target outline;
S2-2-2：将目标轮廓与部件模型库比对，识别出具体的光伏部件。S2-2-2: Compare the target outline with the component model library to identify specific photovoltaic components.
首先通过轮廓的识别方式判断识别出光伏部件的型号等具体信息，获取具体的光伏部件后，能够进行针对性的检查，有利于问题的快速排查。First, the specific information such as the model of the photovoltaic component is determined through the contour recognition method. After obtaining the specific photovoltaic component, targeted inspection can be carried out, which is conducive to rapid troubleshooting of problems.
进一步，所述S3包括：Further, the S3 includes:
S3-1：根据光伏部件，获取该光伏部件的若干检查项目；S3-1: According to the photovoltaic component, obtain several inspection items of the photovoltaic component;
S3-2：结合历史图像信息分析光伏部件的各检查项目的状态。S3-2: Analyze the status of each inspection item of the photovoltaic component based on historical image information.
通过获取该光伏部件的历史图像信息，根据前后图像的对比分析从而判断各检查项目的当前状态。上述方法能比较快速地排查出光伏部件的外部问题，适用于大型光伏站广范围的排查工作。通过图像识别能够对光伏部件进行较全面的外部检查，具体细分为外形完整度、覆盖物、光伏照度和附近杂物等方面。根据可见光图像的轮廓识别和颜色识别的算法能够分析识别该光伏部件的外形完整度百分比，即外形是否存在缺损、形变、锈蚀等情况；光伏部件的覆盖物情况，即部件表面的灰尘、鸟粪、树叶等异物的覆盖情况及覆盖占比；光伏部件附近是否有杂物，如垃圾、零部件、工器具等。通过红外图像能够识别光伏部件的实时光伏照度，根据光伏照度图像的前后差异，能够识别该光伏部件上的热斑情况及热斑位置。By obtaining historical image information of the photovoltaic component, the current status of each inspection item can be determined based on comparative analysis of the before and after images. The above method can quickly identify external problems of photovoltaic components and is suitable for a wide range of inspections of large photovoltaic stations. Through image recognition, a more comprehensive external inspection of photovoltaic components can be carried out, which is subdivided into aspects such as shape integrity, covering, photovoltaic illumination and nearby debris. The algorithm based on the contour recognition and color recognition of visible light images can analyze and identify the percentage of shape integrity of the photovoltaic component, that is, whether there are defects, deformations, rusts, etc. in the shape; the covering condition of the photovoltaic component, that is, dust and bird droppings on the surface of the component The coverage and proportion of foreign objects such as leaves and leaves; whether there are debris near the photovoltaic components, such as garbage, parts, tools, etc. The real-time photovoltaic illumination of photovoltaic components can be identified through infrared images. According to the difference before and after the photovoltaic illumination images, the hot spots and hot spot locations on the photovoltaic components can be identified.
进一步，所述S4包括：Further, the S4 includes:
S4-1：根据光伏部件的状态生成若干维护方案；S4-1: Generate several maintenance plans based on the status of photovoltaic components;
S4-2：获取光照情况，根据光照情况选择维护方案。S4-2: Obtain the lighting conditions and select a maintenance plan based on the lighting conditions.
根据光伏部件的各检查项目的状态，生成多个相应的维护方案，然后根据光照情况来选择具体的维护方案，以避免在维护的过程中影响光伏电站的发电效率，避免造成额外的经济损失。 According to the status of each inspection item of photovoltaic components, multiple corresponding maintenance plans are generated, and then specific maintenance plans are selected according to the lighting conditions to avoid affecting the power generation efficiency of the photovoltaic power station during the maintenance process and avoiding additional economic losses.
进一步，所述S3还包括：Further, the S3 also includes:
S3-3：根据各检查项目的状态，计算光伏部件的预测发电损耗量；S3-3: Calculate the predicted power generation loss of photovoltaic components based on the status of each inspection item;
S3-4：比较预测发电损耗量和实际发电损耗量，分析发电损耗原因；S3-4: Compare the predicted power generation loss with the actual power generation loss, and analyze the causes of power generation loss;
S3-5：根据发电损耗原因，分析光伏部件的状态；S3-5: Analyze the status of photovoltaic components based on the causes of power generation loss;
所述发电损耗原因包括外部原因和内部原因，所述光伏部件的状态包括外部状态和内部状态。The causes of power generation loss include external causes and internal causes, and the status of the photovoltaic component includes external status and internal status.
通过上述步骤从图像分析中识别出了光伏部件的外部状态后，还需要进一步分析当前发电量异常是否完全由以上外部原因引起，如果不能排查处外部原因之外的内部问题，后续的维护方案还是无法完全解决光伏部件的发电损耗问题。因此需要根据光伏部件外部状态结合历史数据计算预测发电损耗量，将计算的预测发电损耗量与实际发电损耗量进行比较分析，若两者差距不大，则判断本次发电损耗量为外部原因引起，若两者差距较大，则判断除了外部原因还有光伏部件内部原因引起发电量损耗，在确认外部原因的问题后，还需要对具体的内部原因进行分析。根据内外两方面原因，分析得到光伏部件的外部状态和内部状态，统计光伏部件的内外状态便于后续步骤针对光伏部件的内外状态生成相应的维护方案。After the external status of the photovoltaic components is identified from the image analysis through the above steps, it is necessary to further analyze whether the current abnormal power generation is entirely caused by the above external reasons. If internal problems other than external reasons cannot be investigated and resolved, the subsequent maintenance plan is still The problem of power generation loss of photovoltaic components cannot be completely solved. Therefore, it is necessary to calculate the predicted power generation loss based on the external status of the photovoltaic components and historical data, and compare and analyze the calculated predicted power generation loss with the actual power generation loss. If the difference between the two is not large, it is judged that the power generation loss is caused by external reasons. , if the difference between the two is large, it is judged that in addition to external causes, there are also internal causes of photovoltaic components that cause power generation loss. After confirming the external causes, the specific internal causes need to be analyzed. Based on the internal and external reasons, the external and internal states of the photovoltaic components are analyzed and the internal and external states of the photovoltaic components are counted to facilitate the subsequent steps to generate corresponding maintenance plans for the internal and external states of the photovoltaic components.
本发明还提供光伏发电智能运维系统，该系统采用了上述光伏发电智能运维方法。The present invention also provides a photovoltaic power generation intelligent operation and maintenance system, which adopts the above-mentioned photovoltaic power generation intelligent operation and maintenance method.
本发明还提供一种计算机可读存储介质，所述存储介质上存储有计算机程序，当所述计算机程序被处理器执行时，实现上述光伏发电智能运维方法。The present invention also provides a computer-readable storage medium. A computer program is stored on the storage medium. When the computer program is executed by a processor, the above-mentioned intelligent operation and maintenance method for photovoltaic power generation is implemented.
附图说明Description of drawings
图1为本发明实施例的光伏发电智能运维方法的逻辑框图。Figure 1 is a logical block diagram of the intelligent operation and maintenance method of photovoltaic power generation according to an embodiment of the present invention.
具体实施方式Detailed ways
下面将结合附图对本发明技术方案的实施例进行详细的描述。以下实施例仅用于更加清楚地说明本发明的技术方案，因此只作为示例，而不能以此来限制本发明的保护范围。The embodiments of the technical solution of the present invention will be described in detail below with reference to the accompanying drawings. The following examples are only used to illustrate the technical solutions of the present invention more clearly, and are therefore only examples and cannot be used to limit the scope of the present invention.
需要注意的是，除非另有说明，本申请使用的技术术语或者科学术语应当为本发明所属领域技术人员所理解的通常意义。It should be noted that, unless otherwise stated, the technical terms or scientific terms used in this application should have the usual meanings understood by those skilled in the art to which this invention belongs.
实施例一：Example 1:
如图1所示，本实施例公开了光伏发电智能运维方法，具体包括以下步骤(本方案中对各步骤的编号仅做步骤区分作用，不限制各步骤的具体执行顺序，且各步骤还可同时进行)： As shown in Figure 1, this embodiment discloses a photovoltaic power generation intelligent operation and maintenance method, which specifically includes the following steps (the numbers of each step in this solution are only used to distinguish the steps and do not limit the specific execution order of each step, and each step also Can be performed simultaneously):
S1-1：获取光伏的发电量数据。获取光伏电站近期的发电量数据。S1-1: Obtain photovoltaic power generation data. Obtain the recent power generation data of the photovoltaic power station.
S1-2：分析发电量数据，识别发电量异常的光伏发电区域。以区域为单位，将最近的发电量数据与往日发电量数据分析对比，根据发电量的衰减比例，判断该光伏发电区域的发电量是否异常。S1-2: Analyze the power generation data and identify photovoltaic power generation areas with abnormal power generation. Taking the area as a unit, the recent power generation data is analyzed and compared with the past power generation data, and based on the attenuation ratio of the power generation, it is judged whether the power generation of the photovoltaic power generation area is abnormal.
S1-3：采集发电量异常的光伏发电区域的图像信息。确定发电量异常的光伏发电区域后，通过无人机的动态摄像头或该光伏发电区域的固定式监控摄像头，对光伏发电区域的图像进行采集，进行图像采集的摄像头包括可见光摄像头和红外摄像头，能够分别采集可见光图像和红外图像。本实施例中采集的图像主要为户外的光伏板等部件。S1-3: Collect image information of photovoltaic power generation areas with abnormal power generation. After determining the photovoltaic power generation area with abnormal power generation, collect images of the photovoltaic power generation area through the dynamic camera of the drone or the fixed surveillance camera of the photovoltaic power generation area. The cameras for image collection include visible light cameras and infrared cameras, which can Visible light images and infrared images are collected separately. The images collected in this embodiment are mainly outdoor photovoltaic panels and other components.
S2-1：对图像信息进行清晰化处理，所述清晰化处理为对图像逐帧分析，选取色差最小的若干张图像，通过图像多帧融合算法，生成环境光稳定的图像，并增强图像的对比度和色彩。初步采集的图像通常比较模糊，存在清晰度不足的问题，影响下一步分析识别。本实施例中主要针对光伏发电现场环境光闪烁导致采集的图像不清晰的问题，对采集的图像信息分析，选取色差最小的几张图像，通过图像多帧融合算法，将不同时刻多帧图像对应像素点的灰度值相加，求取它们的时间均值图像，当所观察目标的环境照度太低，会导致目标能量小，噪声大，图像信噪比降低。对静态的图像序列，利用各帧信号的相关性和噪声的不相关性，采用序列图像多帧累加技术，可大大改善图像的信噪比，提高清晰度，生成环境光稳定的图像，再增强图像对比度，增强色彩，便于后续的识别过程。同时，对无人机航拍的图像进行透视畸变矫正处理。S2-1: Perform a clearing process on the image information. The clearing process is to analyze the image frame by frame, select several images with the smallest color difference, and use a multi-frame image fusion algorithm to generate an image with stable ambient light and enhance the image quality. Contrast and color. The initially collected images are usually blurry and lack clarity, which affects the next step of analysis and identification. This embodiment mainly aims at the problem of unclear collected images caused by flickering of ambient light at the photovoltaic power generation site. The collected image information is analyzed, several images with the smallest color difference are selected, and the multi-frame image fusion algorithm is used to correspond to the multi-frame images at different times. The gray values of the pixels are added together to obtain their time-average image. When the ambient illumination of the observed target is too low, it will result in low target energy, high noise, and reduced image signal-to-noise ratio. For static image sequences, utilizing the correlation of each frame signal and the non-correlation of noise, using sequence image multi-frame accumulation technology can greatly improve the signal-to-noise ratio of the image, improve the clarity, generate an image with stable ambient light, and then enhance it. Image contrast, enhanced color, facilitates the subsequent recognition process. At the same time, perspective distortion correction is performed on the aerial images taken by the drone.
S2-2-1：分析清晰化处理后的图像信息，获取目标轮廓。对处理后的图像信息逐层进行，获取图像中的目标轮廓曲线。S2-2-1: Analyze the sharpened image information and obtain the target contour. The processed image information is processed layer by layer to obtain the target contour curve in the image.
S2-2-2：将目标轮廓与部件模型库比对，识别出具体的光伏部件。将目标轮廓曲线与数据库的模型部件库比对，通过图像相似度匹配和BP神经网络算法，识别出该处光伏设备的具体型号，例如光伏板、汇流箱、逆变器等部件。S2-2-2: Compare the target outline with the component model library to identify specific photovoltaic components. Compare the target contour curve with the model component library of the database, and identify the specific model of the photovoltaic equipment there, such as photovoltaic panels, combiner boxes, inverters and other components through image similarity matching and BP neural network algorithms.
S3-1：根据光伏部件，获取该光伏部件的若干检查项目。识别出具体的光伏部件，根据光伏部件具体型号的运维规程，获取该光伏部件的主要检查项目，整理成检查项目列表，本实施例中主要的检查项目包括光伏部件的外形完整度、覆盖物、光伏照度和附近杂物。例如识别的光伏部件为光伏板，则根据该光伏板的具体型号的运维规程，对光伏板的外形、覆盖 物和光伏照度等项目进行进一步的检查。S3-1: According to the photovoltaic component, obtain several inspection items of the photovoltaic component. The specific photovoltaic component is identified, and the main inspection items of the photovoltaic component are obtained according to the operation and maintenance procedures of the specific model of the photovoltaic component, and organized into a list of inspection items. In this embodiment, the main inspection items include the appearance integrity and covering of the photovoltaic component. , photovoltaic illumination and nearby debris. For example, if the identified photovoltaic component is a photovoltaic panel, the shape, coverage, and Further inspections will be conducted on items such as objects and photovoltaic illumination.
S3-2：结合历史图像信息分析光伏部件的各检查项目的状态。上述检查项目主要通过获取该光伏部件的历史图像信息，根据前后图像的对比分析从而判断各检查项目的当前状态。本实施例中以光伏板为检查对象，根据可见光图像的轮廓识别和颜色识别的算法能够分析识别该光伏部件的外形完整度百分比，即外形是否存在缺损、形变、锈蚀等情况；光伏部件的覆盖物情况，即光伏板表面的灰尘、鸟粪、树叶等异物的覆盖情况及覆盖占比；光伏部件附近是否有杂物，如垃圾、零部件、工器具等。通过红外图像能够识别光伏板的实时光伏照度，根据光伏照度图像的前后差异，能够识别该光伏板上的热斑情况及热斑位置。S3-2: Analyze the status of each inspection item of the photovoltaic component based on historical image information. The above inspection items mainly obtain the historical image information of the photovoltaic component, and judge the current status of each inspection item based on the comparative analysis of the before and after images. In this embodiment, the photovoltaic panel is used as the inspection object. The algorithm of contour recognition and color recognition of the visible light image can analyze and identify the shape integrity percentage of the photovoltaic component, that is, whether there are defects, deformations, rusts, etc. in the shape; the coverage of the photovoltaic component The condition of objects, that is, the coverage and proportion of foreign objects such as dust, bird droppings, leaves, etc. on the surface of the photovoltaic panels; whether there are debris near the photovoltaic components, such as garbage, parts, tools, etc. The real-time photovoltaic illumination of the photovoltaic panel can be identified through infrared images. According to the difference before and after the photovoltaic illumination image, the hot spot condition and hot spot location on the photovoltaic panel can be identified.
S4-1：根据光伏部件的状态生成若干维护方案。根据光伏部件的各检查项目的状态，生成多个相应的维护方案，例如针对光伏板上覆盖物的问题，在维护的过程中可以选择抹布清洁或冲洗清洁，选择冲洗清洁的水温等，具体的方案选择还需要进行后续判断。S4-1: Generate several maintenance plans based on the status of photovoltaic components. According to the status of each inspection item of the photovoltaic components, multiple corresponding maintenance plans are generated. For example, for the problem of covering on the photovoltaic panels, during the maintenance process, you can choose rag cleaning or flushing cleaning, select the water temperature for flushing and cleaning, etc., specific Plan selection also requires subsequent judgment.
S4-2：获取光照情况，根据光照情况选择维护方案。本实施例中获取的光照情况包括光照角度和光伏温度。根据光照情况来选择具体的维护方案主要是为了避免在维护的过程中影响光伏电站的发电效率，避免造成额外的经济损失。例如在上述针对光伏板上覆盖物的问题生成的维护方案中存在抹布清洁或冲洗清洁的方案，首先获取当前光照角度，比较光照角度和光伏阵列朝向角度的重合度，若重合度较高(差值角度15度以内)，则当前的光照角度为直射光，为防止清洁过程中因为人为阴影带来光伏阵列发电量损失，甚至发生热斑效应损坏光伏阵列，在光照角度为直射光的情况下选择冲洗清洁，即在远处冲水进行冲洗，尽量避免人为遮挡对光伏阵列造成影响。若当前光照角度和光伏阵列朝向角度的重合度较低(差值角度超过15度)，则当前的光照角度为散射光，光照对光伏阵列没有直射，则可以采用清洁效果更细致的抹布清洁，清洗过程一般使用清水，配合柔性毛刷或抹布来进行清洁。同时，还需要根据需要当前光伏温度选择合适的清洁水温，在中午等光照较好的时候光伏阵列组件表面温度较高，与冷水直接接触可能引起玻璃或组件损伤，因此还需获取光伏组件的表面温度，根据光伏表面温度选择合适的清洁水温，本实施例中光伏表面温度与清洁水温的温差不大于8℃即可，能够避免温差过大对光伏板造成不可逆的损害。S4-2: Obtain the lighting conditions and select a maintenance plan based on the lighting conditions. The illumination conditions obtained in this embodiment include illumination angle and photovoltaic temperature. Choosing specific maintenance plans based on light conditions is mainly to avoid affecting the power generation efficiency of the photovoltaic power station during the maintenance process and avoid causing additional economic losses. For example, in the maintenance plan generated above for the problem of covering on photovoltaic panels, there is a rag cleaning or flushing cleaning plan. First, the current illumination angle is obtained, and the coincidence degree of the illumination angle and the orientation angle of the photovoltaic array is compared. If the coincidence degree is high (difference) value angle within 15 degrees), the current illumination angle is direct light. In order to prevent the loss of photovoltaic array power generation due to artificial shadows during the cleaning process, or even damage to the photovoltaic array due to the hot spot effect, when the illumination angle is direct light Choose flush cleaning, that is, flush with water from a distance to avoid the impact of artificial occlusion on the photovoltaic array. If the overlap between the current illumination angle and the orientation angle of the photovoltaic array is low (the difference angle exceeds 15 degrees), then the current illumination angle is scattered light and the light does not directly illuminate the photovoltaic array. You can use a rag with a more detailed cleaning effect to clean. The cleaning process generally uses clean water and a flexible brush or rag for cleaning. At the same time, it is also necessary to select the appropriate cleaning water temperature according to the current photovoltaic temperature. At noon and other times when the light is better, the surface temperature of the photovoltaic array module is higher. Direct contact with cold water may cause damage to the glass or components, so it is also necessary to obtain the surface of the photovoltaic module. Temperature, select the appropriate cleaning water temperature according to the photovoltaic surface temperature. In this embodiment, the temperature difference between the photovoltaic surface temperature and the cleaning water temperature is no more than 8°C, which can avoid irreversible damage to the photovoltaic panels caused by excessive temperature differences.
实施例二：Example 2:
本实施例与实施例一不同之处在于，步骤S3还包括以下步骤： The difference between this embodiment and Embodiment 1 is that step S3 also includes the following steps:
S3-3：根据各检查项目的状态，计算光伏部件的预测发电损耗量。通过上述步骤从图像分析中识别出了光伏部件的外部状态，例如光伏板的外形完整度、表面覆盖物情况和周围杂物等。接下来需要进一步分析当前发电量异常是否完全由以上外部原因引起，因此需要根据光伏部件外部状态结合历史数据计算预测发电损耗量。例如此时光伏板有近二分之一的面积被树木阴影等其他杂物遮挡，导致该面积的光伏板难以接触阳光，因此在历史发电数据中选取该光伏板没有被遮挡的时候，且天气、光照和温度等其他条件相似的情况下，计算该光伏板历史发电量的一半为预测发电损耗量(因光伏板有近二分之一的面积被遮挡)，该预测发电损耗量用于后续损耗原因的判断。S3-3: Calculate the predicted power generation loss of photovoltaic components based on the status of each inspection item. Through the above steps, the external status of the photovoltaic component is identified from the image analysis, such as the shape integrity of the photovoltaic panel, surface coverage, and surrounding debris. Next, it is necessary to further analyze whether the current abnormal power generation is entirely caused by the above external reasons. Therefore, it is necessary to calculate and predict the power generation loss based on the external status of the photovoltaic components combined with historical data. For example, at this time, nearly one-half of the area of the photovoltaic panel is blocked by tree shadows and other debris, making it difficult for the photovoltaic panel in this area to access sunlight. Therefore, select a time when the photovoltaic panel is not blocked in the historical power generation data, and the weather , light and temperature and other similar conditions, calculate half of the historical power generation of the photovoltaic panel as the predicted power generation loss (because nearly one-half of the area of the photovoltaic panel is blocked), and the predicted power generation loss will be used for subsequent Determination of cause of loss.
S3-4：比较预测发电损耗量和实际发电损耗量，分析发电损耗原因。将计算的预测发电损耗量与实际发电损耗量进行比较分析，例如因光伏板遮挡原因的预测发电损耗量的变化规律是否符合实际发电损耗量，若两者差距不大，则判断本次发电损耗量为外部原因引起，若两者差距较大，则判断除了外部原因还有光伏部件内部原因引起发电量损耗，在确认外部原因的问题后，还需要对具体的内部原因进行分析，根据预测发电损耗量和实际发电损耗量的差值，结合历史数据对该差值进行分析，包括差值产生时间、变化趋势等方面分析产生该差值的原因，包括逆变器效率降低、线路损耗增大、光伏板老化等。S3-4: Compare the predicted power generation loss with the actual power generation loss, and analyze the causes of power generation loss. Compare and analyze the calculated predicted power generation loss with the actual power generation loss. For example, whether the change pattern of the predicted power generation loss due to photovoltaic panel shading is consistent with the actual power generation loss. If the difference between the two is not large, then the current power generation loss is judged. The amount is caused by external causes. If the difference between the two is large, it is judged that in addition to external causes, there are also internal causes of the photovoltaic components that cause the loss of power generation. After confirming the external causes, it is also necessary to analyze the specific internal causes and predict power generation based on The difference between the loss and the actual power generation loss is analyzed based on historical data, including the time when the difference occurred, changing trends, etc. Analysis of the reasons for the difference, including reduced inverter efficiency and increased line losses , photovoltaic panel aging, etc.
S3-5：根据发电损耗原因，分析光伏部件的状态。发电损耗原因包括根据图像识别得到的外部原因和数据分析得到的内部原因，根据内外两方面原因，分析得到光伏部件的外部状态和内部状态。例如当前光伏板外部有二分之一的面积被遮挡，内部存在线损较大和光伏板老化的情况，统计光伏部件的内外状态便于后续步骤针对光伏部件的内外状态生成相应的维护方案。本发明方法不仅采用图像识别光伏部件的外部状态，还在此技术上结合实际发电数据分析识别光伏部件的内部是否存在问题，并根据历史数据分析进一步判断光伏部件的内部状态。本方案因为能够更加真实地划分光伏部件内外问题费力，因此能够更精准识别当前的光伏部件状态。S3-5: Analyze the status of photovoltaic components based on the causes of power generation loss. The causes of power generation loss include external causes obtained through image recognition and internal causes obtained through data analysis. Based on both internal and external causes, the external and internal states of the photovoltaic components are analyzed. For example, currently one-half of the external area of photovoltaic panels is blocked, and there are large line losses and aging of photovoltaic panels inside. Statistics of the internal and external status of photovoltaic components will facilitate subsequent steps to generate corresponding maintenance plans based on the internal and external status of photovoltaic components. The method of the present invention not only uses images to identify the external status of photovoltaic components, but also uses this technology to analyze and identify whether there are problems inside the photovoltaic components based on actual power generation data, and further determines the internal status of the photovoltaic components based on historical data analysis. Because this solution can more realistically divide the internal and external problems of photovoltaic components, it can more accurately identify the current status of photovoltaic components.
本实施例还提供光伏发电智能运维系统，该系统采用了上述光伏发电智能运维方法。This embodiment also provides a photovoltaic power generation intelligent operation and maintenance system, which adopts the above photovoltaic power generation intelligent operation and maintenance method.
本实施例还提供一种计算机可读存储介质，所述存储介质上存储有计算机程序，当所述计算机程序被处理器执行时，实现上述光伏发电智能运维方法。This embodiment also provides a computer-readable storage medium. A computer program is stored on the storage medium. When the computer program is executed by a processor, the above-mentioned intelligent operation and maintenance method for photovoltaic power generation is implemented.
以上的仅是本发明的实施例，方案中公知的具体结构及特性等常识在此未作过多描述， 所属领域普通技术人员知晓申请日或者优先权日之前发明所属技术领域所有的普通技术知识，能够获知该领域中所有的现有技术，并且具有应用该日期之前常规实验手段的能力，所属领域普通技术人员可以在本申请得出的启示下，结合自身能力完善并实施本方案，一些典型的公知结构或者公知方法不应当成为所属领域普通技术人员实施本申请的障碍。应当指出，对于本领域的技术人员来说，在不脱离本发明结构的前提下，还可以作出若干变形和改进，这些也应该视为本发明的保护范围，这些都不会影响本发明实施的效果和专利的实用性。本申请要求的保护范围应当以其权利要求的内容为准，说明书中的具体实施方式等记载可以用于解释权利要求的内容。 The above are only embodiments of the present invention, and common knowledge such as the known specific structures and characteristics of the solutions are not described in detail here. A person of ordinary skill in the relevant field knows all the common technical knowledge in the technical field to which the invention belongs before the filing date or priority date, is able to understand all the existing technologies in the field, and has the ability to apply conventional experimental methods before that date, and is a person with ordinary skill in the field. Personnel can perfect and implement this solution based on their own abilities under the inspiration obtained from this application. Some typical well-known structures or methods should not become an obstacle for those of ordinary skill in the art to implement this application. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention. These should also be regarded as the protection scope of the present invention and will not affect the implementation of the present invention. effectiveness and patented practicality. The scope of protection claimed in this application shall be based on the content of the claims, and the specific implementation modes and other records in the description may be used to interpret the content of the claims.

Claims (10)

  1. 光伏发电智能运维方法，其特征在于，包括以下步骤：The intelligent operation and maintenance method of photovoltaic power generation is characterized by including the following steps:
    S1：采集光伏发电区域的图像信息；S1: Collect image information of the photovoltaic power generation area;
    S2：分析图像信息，识别光伏部件；S2: Analyze image information and identify photovoltaic components;
    S3：结合历史图像信息分析光伏部件的状态；S3: Analyze the status of photovoltaic components based on historical image information;
    S4：根据光伏部件的状态生成维护方案。S4: Generate maintenance plans based on the status of photovoltaic components.
  2. 根据权利要求1所述的光伏发电智能运维方法，其特征在于：所述S1包括：The intelligent operation and maintenance method of photovoltaic power generation according to claim 1, characterized in that: said S1 includes:
    S1-1：获取光伏的发电量数据；S1-1: Obtain photovoltaic power generation data;
    S1-2：分析发电量数据，识别发电量异常的光伏发电区域；S1-2: Analyze power generation data and identify photovoltaic power generation areas with abnormal power generation;
    S1-3：采集发电量异常的光伏发电区域的图像信息。S1-3: Collect image information of photovoltaic power generation areas with abnormal power generation.
  3. 根据权利要求1所述的光伏发电智能运维方法，其特征在于：所述S1中通过无人机或监控摄像头采集光伏发电区域的图像信息，所述图像信息包括可见光图像和红外图像。The intelligent operation and maintenance method of photovoltaic power generation according to claim 1, characterized in that: in S1, image information of the photovoltaic power generation area is collected by drones or surveillance cameras, and the image information includes visible light images and infrared images.
  4. 根据权利要求3所述的光伏发电智能运维方法，其特征在于：所述S2包括：The intelligent operation and maintenance method of photovoltaic power generation according to claim 3, characterized in that: the S2 includes:
    S2-1：对图像信息进行清晰化处理，所述清晰化处理为对图像逐帧分析，选取色差最小的若干张图像，通过图像多帧融合算法，生成环境光稳定的图像，并增强图像的对比度和色彩；S2-1: Perform a clearing process on the image information. The clearing process is to analyze the image frame by frame, select several images with the smallest color difference, and use a multi-frame image fusion algorithm to generate an image with stable ambient light and enhance the image quality. contrast and color;
    S2-2：分析清晰化处理后的图像信息，识别光伏部件。S2-2: Analyze the sharpened image information and identify photovoltaic components.
  5. 根据权利要求4所述的光伏发电智能运维方法，其特征在于：所述S2-2包括：The intelligent operation and maintenance method of photovoltaic power generation according to claim 4, characterized in that: said S2-2 includes:
    S2-2-1：分析清晰化处理后的图像信息，获取目标轮廓；S2-2-1: Analyze the sharpened image information and obtain the target contour;
    S2-2-2：将目标轮廓与部件模型库比对，识别出具体的光伏部件。S2-2-2: Compare the target outline with the component model library to identify specific photovoltaic components.
  6. 根据权利要求3所述的光伏发电智能运维方法，其特征在于：所述S3包括：The intelligent operation and maintenance method of photovoltaic power generation according to claim 3, characterized in that: the S3 includes:
    S3-1：根据光伏部件，获取该光伏部件的若干检查项目；S3-1: According to the photovoltaic component, obtain several inspection items of the photovoltaic component;
    S3-2：结合历史图像信息分析光伏部件的各检查项目的状态；S3-2: Analyze the status of each inspection item of photovoltaic components based on historical image information;
    所述S3-1中检查项目包括光伏部件的外形完整度、覆盖物、光伏照度和附近杂物中的一种或多种。The inspection items in S3-1 include one or more of the shape integrity of the photovoltaic component, covering, photovoltaic illumination, and nearby debris.
  7. 根据权利要求3所述的光伏发电智能运维方法，其特征在于：所述S4包括：The intelligent operation and maintenance method of photovoltaic power generation according to claim 3, characterized in that: the S4 includes:
    S4-1：根据光伏部件的状态生成若干维护方案； S4-1: Generate several maintenance plans based on the status of photovoltaic components;
    S4-2：获取光照情况，根据光照情况选择维护方案。S4-2: Obtain the lighting conditions and select a maintenance plan based on the lighting conditions.
  8. 根据权利要求6所述的光伏发电智能运维方法，其特征在于：所述S3还包括：The intelligent operation and maintenance method of photovoltaic power generation according to claim 6, characterized in that: the S3 further includes:
    S3-3：根据各检查项目的状态，计算光伏部件的预测发电损耗量；S3-3: Calculate the predicted power generation loss of photovoltaic components based on the status of each inspection item;
    S3-4：比较预测发电损耗量和实际发电损耗量，分析发电损耗原因；S3-4: Compare the predicted power generation loss with the actual power generation loss, and analyze the causes of power generation loss;
    S3-5：根据发电损耗原因，分析光伏部件的状态；S3-5: Analyze the status of photovoltaic components based on the causes of power generation loss;
    所述发电损耗原因包括外部原因和内部原因，所述光伏部件的状态包括外部状态和内部状态。The causes of power generation loss include external causes and internal causes, and the status of the photovoltaic component includes external status and internal status.
  9. 光伏发电智能运维系统，其特征在于：该系统采用了权利要求1至8任一项所述的光伏发电智能运维方法。A photovoltaic power generation intelligent operation and maintenance system is characterized in that: the system adopts the photovoltaic power generation intelligent operation and maintenance method described in any one of claims 1 to 8.
  10. 一种计算机可读存储介质，其特征在于，所述存储介质上存储有计算机程序，当所述计算机程序被处理器执行时，实现如权利要求1至8任一项所述的光伏发电智能运维方法。 A computer-readable storage medium, characterized in that a computer program is stored on the storage medium. When the computer program is executed by a processor, the intelligent operation of photovoltaic power generation as described in any one of claims 1 to 8 is realized. dimensional method.
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