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物联网技术在光伏阵列故障诊断的应用综述OA

Review on the Application of Internet of Things Technology in Photovoltaic Array Fault Diagnosis

中文摘要英文摘要

目前,全球范围内已安装了大量光伏发电装置,基本都安装在户外,暴露于恶劣的环境条件下,容易发生不同类型的故障.因此,设计智能化、自动化的光伏电站远程监控系统和故障诊断系统至关重要.对光伏阵列故障检测与诊断方法、物联网技术、人工智能在光伏电站中的应用进行了综述.介绍了光伏监测系统的两种类型:集中式和分散式.光伏监测系统的工作流程分为3个阶段:采集层、预处理和记录层、存储和应用层.从视觉成像和电气特征两个方向开展光伏阵列故障诊断研究总结.介绍了最先进的机器学习和深度学习算法,从成本实现、复杂性、准确性、软件适用性和实时应用的可行性等方面进行了比较.最后,指出了这些技术的不足与发展趋势.

Currently,a huge number of photovoltaic plants have been installed worldwide,most of which are installed outdoors and continuously exposed to harsh environmental conditions,making them prone to different types of faults.Therefore,it is crucial to design intelligent and automated remote monitoring systems and fault diagnosis systems for photovoltaic power plants.A review is conducted on the fault detection and diagnosis methods of photovoltaic array,Internet of Things technology,and the application of artificial intelligence in photovoltaic power plants.Two types of photovoltaic monitoring systems are introduced,namely centralized and decentralized.The workflow of photovoltaic monitoring system is divided into three stages,acquisition layer,preprocessing and recording layer,storage and application layer.A summary of research on photovoltaic array fault diagnosis is carried out from two perspectives:visual imaging and electrical characteristics.The most advanced algorithms such as machine learning and deep learning are introduced,and comparisons are made in terms of cost implementation,complexity,accuracy,software suitability,and feasibility of real-time applications.Finally,the shortcomings and development trends of these technologies are pointed out.

郑志祥;高梦宇

南京大鱼半导体有限公司,南京 210031南京航空航天大学 民航学院,南京 210016

信息技术与安全科学

光伏阵列故障类型故障检测与诊断物联网机器学习深度学习

photovoltaic array fault typesfault detection and diagnosisInternet of Thingsmachine learningdeep learning

《机电工程技术》 2026 (10)

8-17,10

10.3969/j.issn.1009-9492.2026.10.002

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