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...

詳細記述

書誌詳細
出版年:Energy Reports
第一著者: 2-s2.0-85160576369
フォーマット: 論文
言語:English
出版事項: Elsevier Ltd 2023
オンライン・アクセス:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85160576369&doi=10.1016%2fj.egyr.2023.05.163&partnerID=40&md5=224a98b3906ba1766f83bf0187d81e4d
その他の書誌記述
要約: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