Intelligent solar panel monitoring system and shading detection using artificial neural networks

Detecting shading in Photovoltaic panels (PV) is crucial for ensuring optimal energy generation. This paper proposes a novel monitoring system that uses Artificial Neural Network (ANN) technology to detect shading and other faults in PV panels. The system is also supervised using an Internet of Thin...

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书目详细资料
发表在:Energy Reports
主要作者: 2-s2.0-85160576369
格式: 文件
语言:English
出版: Elsevier Ltd 2023
在线阅读:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160576369&doi=10.1016%2fj.egyr.2023.05.163&partnerID=40&md5=224a98b3906ba1766f83bf0187d81e4d
实物特征
总结:Detecting shading in Photovoltaic panels (PV) is crucial for ensuring optimal energy generation. This paper proposes a novel monitoring system that uses Artificial Neural Network (ANN) technology to detect shading and other faults in PV panels. The system is also supervised using an Internet of Things (IoT) monitoring platform, which provides real-time data analysis and alerts. The proposed system's main contribution is its ability to detect shading, which can significantly impact energy generation. The ANN technology accurately detects shading and other faults, while the IoT platform enables remote monitoring and data analysis. Overall, this paper presents a valuable contribution to the field of PV monitoring systems by proposing a novel system that detects shading using ANN technology and is supervised using an IoT monitoring platform. The system's ability to accurately detect shading and other faults can significantly improve energy generation efficiency and reduce maintenance costs. © 2023 The Author(s)
ISSN:23524847
DOI:10.1016/j.egyr.2023.05.163