OVERVIEW AND PROSPECT OF INTELLIGENT DETECTION OF HOT SPOT EFFECT OF PHOTOVOLTAIC MODULES

被引：0

作者：

Wang D. ^{[1
]}

Yao C. ^{[1
]}

Li C. ^{[1
]}

Wang W. ^{[2
]}

Qin B. ^{[3
]}

Zhu R. ^{[1
]}

机构：

[1] College of Energy and Mechanical Engineering, Shanghai University of Electric Power, Shanghai

[2] 21ST Research Institute of China Electronic Technology Group Corporation, Shanghai

[3] Gaussian Robotics, Shanghai

来源：

Taiyangneng Xuebao/Acta Energiae Solaris Sinica | 2024年 / 45卷 / 05期

关键词：

deep learning; hot spot; infrared imaging; intellectualization; PV modules; solar power generation;

D O I：

10.19912/j.0254-0096.tynxb.2023-0042

中图分类号：

学科分类号：

摘要：

In view of the many and complicated problems in the current hot spot detection methods of photovoltaic modules，summarizes and systematically analyzes the existing traditional and intelligent hot spot detection methods for PV modules at home and abroad. And the latest progress of applying deep learning algorithms to them. Focusing on the application of various neural networks，attention mechanisms and target detection models to the detection of hot spot infrared images，such as multi-scale CNN，SpotFPN-based multi-scale feature learning modules etc. After that，experiments are conducted to compare the intelligent diagnostic techniques for hot spot detection of PV modules. Finally，the current issues are discussed and the future progress of the technology is expected. © 2024 Science Press. All rights reserved.

引用

页码：527 / 536

页数：9

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