This proposed method can accurately segment the PV panels and then identify different sizes of hot-spot defects on the PV panels. Lou Y, Li X, and Lin H Detection method of photovoltaic panel defect based on improved mask r-cnn J. Internet Technol. 2022 23 2 397-406. Crossref. Google Scholar [9] Zhang M and Yin L Solar cell surface defect
View moreAbstract: Hot spot in photovoltaic panels has destructive impact on the system, which results in early degradation and [14], a hot spot detection and suppression method has been proposed. Hot spot is detected using a model based technique. Then, the best MPP is determined to moderate the stress of the hot spotted cells.
View moreThis paper presents an active hot-spot detection method to detect hot spotting within a series of PV cells, using ac parameter characterization. A PV cell is comprised of
View moreAlso, an efficient method is utilised for protection of the panels against hot spotting. The detection method is based on equivalent DC impedance (EDCI) of the panel''s strings, which has useful signatures for hot spot detection. The EDCI monitoring of the panel''s strings is performed using a current sensor and several simple resistive voltage
View moreDownload Citation | On May 26, 2023, Lijuan Liu and others published An Efficient Hot Spot Detection Method with Small Sample Learning for Photovoltaic Panels | Find, read and cite all the
View moreHot spot in photovoltaic panels has destructive impact on the system, which results in early degradation and even permanent damage of panels. Using conventional bypass diode to prevent hot spotting is not a perfect remedy and more efficient techniques are necessary. In this study, a simple technique is proposed for detection of hot spotting. Also, an efficient
View moreThe existing hot-spot fault detection methods of photovoltaic panels cannot adequately complete the real-time detection task; hence, a detection model considering both Keywords: photovoltaic panels; hot spot; failure detection; neural network 1. Introduction In July 2021, SolarPower Europe issued The Global Market Outlook Report for 2021
View moreExperimental results show that the improved algorithm achieves an average detection accuracy of 79.98% for hot spot faults on photovoltaic panels, which is 1.82% higher than that of the original
View moreIn this paper, the defect detection of PV modules based on supervised learning is concerned. For PV modules, the commonly used defect detection methods can be divided into two categories, which are the electrical-parameter-based methods and the infrared-image-based methods. 2.1.1 PV module defect detection based on the electrical parameters
View moreHot spot in photovoltaic panels has destructive impact on the system, which results in early degradation and even permanent damage of panels., an interesting active
View moreA BpD also serves as a protective device to prevent module destruction in case of a hot spot fault or other faults that The measured parameters in Table 2 should be considered before the methods of PV fault detection and classification Mahendran et al. (2015) used an Arduino microcontroller to measure PV panel voltage, PV temperature
View moreSwitching PV panels by adding controlled electronic circuits is a usual approach for both arcing and mismatch defects protections [17]. Recently, this technique has also been used for HS
View moreWith the rapid development of photovoltaic power stations, various faults frequently occur during the maintenance of photovoltaic panels. The hot spot is one of the critical issues which is not easy to observe and has a tremendously harmful impact. Traditional graph target recognition training requires a large amount of data in practical applications. However, there are many issues with
View moreA bright spot detection and analysis method for infrared photovoltaic panels based on image processing Jun Liu1,2* and Ning Ji2 1Institute of Logistics Science and Engineering, Shanghai Maritime
View moreThe detection of hot spot defects in photovoltaic power plants is a key step in ensuring the constructed hot spot detection method is based on large pho panels by radiometric sensors embe
View morePhotovoltaic power generation is clean and environmentally friendly, and has been widely used. Hot spots on photovoltaic panels, caused by shading and leading to heating, reduce the efficiency of photovoltaic power generation and even damage the panels. To address the problem of low detection accuracy in existing models for hot spot detection on photovoltaic
View moreThe hot spot effect is an important factor that affects the power generation performance and service life in the power generation process. To solve the problems of low
View moreaccuracy in existing models for hot spot detection on photovoltaic panels, a method for detecting hot spot faults on photovoltaic panels, called SK-FRCNN (Selective Kernel-Faster RCNN), based on the Faster RCNN network is proposed. The feature extraction module in the Faster RCNN network uses an attention
View moreThis article proposes a Deeplab-YOLO hot-spot defect detection method that combines segmentation and detection with infrared images and based on the differences and
View moreTo solve the problems of the hot spot effect of photovoltaic modules and surface temperature detection of photovoltaic panels, a detection scheme that uses wavelength
View moreAbstract: Hot spots caused by photovoltaic (PV) panel faults significantly impact their power generation efficiency and safety. Current PV hot spot detection methods face challenges such as low detection rates for small targets and poor generalization. To address these issues, this paper proposes a PV panel hot spot detection method based on image processing.
View moreAt present, it is difficult to detect the photovoltaic (PV) hot spots and the recognition efficiency is low. In this paper, an improved Single Shot MultiBox Detector (SSD) algorithm was designed for PV hot spot detection. The algorithm used the MobileNet network to replace the VGG16 convolutional neural network structure in the original SSD.
View moreAs an important component of photovoltaic power generation, PV panels play a crucial role in the photovoltaic power generation industry. In order to overcome the current problem of low speed and accuracy in detecting hot spot faults of PV panels in photovoltaic power plants, this paper proposes a lightweight YOLO V5 model to realize the detection of hot spot defects of PV
View moreAccurate classification and detection of hot spots of photovoltaic (PV) panels can help guide operation and maintenance decisions, improve the power generation efficiency of the PV system, and
View moreTo address this issue, this paper proposes a method and system for hot spot detection on photovoltaic panels using unmanned aerial vehicles (UAVs) equipped with multispectral cameras. The UAVs capture visible and infrared images of the photovoltaic power plant, which are then processed for photogrammetry to determine imaging position and attitude.
View moreThis model is a detection method for hot spots of PV panels based on the latest generation of the one-stage object detection YOLOv5 network, which is improved to achieve
View moreHotspot defect detection (HDD) of photovoltaic (PV) modules is one of the daily inspections of PV power stations. It aims to detect hotspot defects from the infrared images
View moreIn this study, a simple technique is proposed for detection of hot spotting. Also, an efficient method is utilised for protection of the panels against hot spotting. The detection method is based on equivalent DC impedance (EDCI) of the panel''s strings, which has useful signatures for hot spot detection. The EDCI monitoring of the panel''s
View moreThe invention discloses a method for detecting hot spots of a photovoltaic panel, a storage medium and electronic equipment, wherein the method acquires an infrared image of the photovoltaic panel; dividing an infrared image of the photovoltaic panel by using a pre-trained image division light model to obtain an infrared image of the photovoltaic module, wherein the
View moreIn [ 10 ], an interesting active method for hot spot detection has been presented based on measurement of DC and AC impedances of PV panels. It is shown that under MPPT control, hot spotting in a single cell results in DC and AC impedances increase. The AC impedance is detected using a signal at 10–70 kHz frequency range.
This article proposes a Deeplab-YOLO hot-spot defect detection method that combines segmentation and detection with infrared images and based on the differences and features in the shape, size, and color of PV panels and hot spots. On the one hand, it can meet the accuracy of segmentation and enhance the edge features of the target.
Aiming at the problem of difficult operation and maintenance of PV power plants in complex backgrounds and combined with image processing technology, a method for detecting hot spot defects in infrared image PV panels that combines segmentation and detection, Deeplab-YOLO, is proposed.
The hotspot defect detection (HDD) of PV modules is to detect hotspot defects from the infrared images (IFIs), which are captured by the unmanned aerial vehicles (UAV) at about 20 ms. The IFIs have the next characteristics: the image backgrounds are complex, a large number of disturbed heat sources are existed, and the size of hotspots are tiny.
The detection method is based on equivalent DC impedance (EDCI) of the panel's strings, which has useful signatures for hot spot detection. The EDCI monitoring of the panel's strings is performed using a current sensor and several simple resistive voltage dividers. After the detection, hot spotted string is open circuited using a two-state relay.
To prevent a hot spot in a PV (Photovoltaic) module, opening the circuit of the substring containing the mismatched cell is an effective method. This is because no current or power will flow through any cell in the PV substring when the module is bypassed, thereby preventing hot spotting. Once a hot spot is detected, this approach ensures no net output power is produced.
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