Voltage-based hot-spot detection method for PV string using projector

Wang, Yadong; Itako, Kazutaka; Kudoh, Tomohiro; Koh, Keishin; Ge, Qiang

doi:10.1109/icpre.2016.7871140

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…In addition, since the conventional bypass diode also cannot effectively remove the hot spot fault, Wang, Y.D. et al [7] proposed a hot spot detection method for PV arrays based on the mismatch detection technique, which achieves hot spot detection by measuring the equivalent DC impedance of the PV array and combining it with the mismatch detection technique, in addition to using a relay to clear the hot spot fault. The method is able to clear hot spot faults in a timely manner, but requires the addition of a relay for each PV array, which makes the detection cost slightly higher for large PV plants.…”

Section: Introductionmentioning

confidence: 99%

Hot Spot Detection of Photovoltaic Module Infrared Near-field Image based on Convolutional Neural Network

Fan

Zhang

et al. 2022

J. Phys.: Conf. Ser.

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With the installation and use of large-scale photovoltaic systems around the world, the detection of photovoltaic system operation and maintenance has become increasingly important. This research uses a convolutional neural network training model to detect and classify the infrared near-field images of photovoltaic modules from small-scale photovoltaic plants in the laboratory. This model classifies the images into two categories: with and without hot spots, with a classification accuracy of 96.58%. The experimental results show that the convolutional neural network training model has a good classification result

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Section: Introductionmentioning

confidence: 99%

Hot Spot Detection of Photovoltaic Module Infrared Near-field Image based on Convolutional Neural Network

Fan

Zhang

et al. 2022

J. Phys.: Conf. Ser.

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“…With the completion and operation of a large number of PV power stations, the demand for their operation and maintenance continues to be strong, and the defect detection algorithm for PV modules [2] has become a research hotspot. Defect detection algorithms for PV are mainly divided into two categories: detection methods based on electrical characteristics monitoring [3][4] and detection methods based on thermal infrared images [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

“…The hot spot detection can be realized by counting and analyzing the current variation. Wang et al [4] realized hot spot detection by measuring the equivalent DC impedance of the PV array and combining with the mismatch detection technology. The realization principle of this type of method is simple, but for large-scale PV power plants, thousands of sensors are required to complete data acquisition, which is costly.…”

Section: Introductionmentioning

confidence: 99%

Research on defect detection algorithm of photovoltaic modules based on improved Yolov5

Liu¹,

Yu²,

Liu³

et al. 2022

Second International Conference on Testing Technology and Automation Engineering (TTAE 2022)

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With the vigorous development of the solar photovoltaic industry, the operation and maintenance of photovoltaic power stations has ushered in huge challenges. To solve the problems of low efficiency, poor accuracy, and high cost of traditional manual inspection of photovoltaic power stations, the UAV inspection system for photovoltaic has become a new solution to solve the pain points of the industry, which can improve the inspection efficiency greatly. In photovoltaic inspection systems, defect detection is the most important goal. In this paper, a defect detection algorithm based on improved yolov5 for photovoltaic modules is proposed. The convolution block attention module (CBAM) is introduced to extract the attention area, and the weighted non-maximum suppression (NMS) is replaced by DIOU_NMS to improve the recognition accuracy of the model. The experimental results show that the algorithm can effectively identify the hot spots and diode defects of photovoltaic modules, which lays a solid foundation for the fully autonomous inspection of photovoltaic power stations.

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“…cannot be monitored on these studies while PV system is operating. Previously, the authors developed Hot-Spot detection method to module before installation using projector [6,7]. However, Hot-Spot always occurs because of various factors even if the module is normal at checking for a Hot-Spot.…”

Section: Introduction mentioning

confidence: 99%

Hot-Spot Detection System with Correction of Operating Point for PV Generation System

Itako¹,

Iiduka²,

Kudoh³

et al. 2017

JEPE

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Currently, the production and the number of installations of PV (photovoltaic) modules have been increasing rapidly because of a feed-in tariff in Japan. Accordingly, the number of failures has also increased. Many failures are a result of the Hot-Spot phenomenon in which defective cell becomes hot when shadow occurs on the cell. On the other hand, if shadow occurs on normal cell, there are cases that P&O method that is MPPT (maximum power point tracking) control method incorporated in conventional PV system cannot track maximum power point and generated power decreases. The correspondence is required rapidly if these trouble occur. However, conventional PV system monitors generated power, correspondence is impossible by monitoring generated power. Previously, the authors developed real time Hot-Spot detection system that incorporates into PCS (power conditioning system). Thus, the authors developed plug-in type Hot-Spot monitoring system that includes "PV peak shift method" and confirmed effectiveness of the system in this time. "PV peak shift method" loads "Scan method" that is MPPT control method and measures I-V (current-voltage) characteristic by changing voltage of module from open to short by "Scan method" on a regular basis. The developed Hot-Spot monitoring system uses slope of I-V characteristic of PV module. Inserting developed system into already installed PV system, Hot-Spot can be easily monitored in real time and PV system can be operated at maximum power point.

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Voltage-based hot-spot detection method for PV string using projector

Cited by 7 publications

References 4 publications

Hot Spot Detection of Photovoltaic Module Infrared Near-field Image based on Convolutional Neural Network

Hot Spot Detection of Photovoltaic Module Infrared Near-field Image based on Convolutional Neural Network

Research on defect detection algorithm of photovoltaic modules based on improved Yolov5

Hot-Spot Detection System with Correction of Operating Point for PV Generation System

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