Cover Image

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 Th...

Full description

Saved in:
Bibliographic Details
Main Authors: M. Abdallah, Fahad Saleh, Abdullah, M.N., Musirin, Ismail, M. Elshamy, Ahmed
Format: Article
Language:English
Published: Elsevier 2023
Subjects:
T Technology (General)
Online Access:http://eprints.uthm.edu.my/9619/1/J16143_eac313c9cbc1fdd5c22b7e6ec3a3d051.pdf
http://eprints.uthm.edu.my/9619/
https://doi.org/10.1016/j.egyr.2023.05.163
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.uthm.eprints.9619
record_format eprints
spelling my.uthm.eprints.96192023-08-16T07:08:55Z http://eprints.uthm.edu.my/9619/ Intelligent solar panel monitoring system and shading detection using artificial neural networks M. Abdallah, Fahad Saleh Abdullah, M.N. Musirin, Ismail M. Elshamy, Ahmed T Technology (General) 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. Elsevier 2023 Article PeerReviewed text en http://eprints.uthm.edu.my/9619/1/J16143_eac313c9cbc1fdd5c22b7e6ec3a3d051.pdf M. Abdallah, Fahad Saleh and Abdullah, M.N. and Musirin, Ismail and M. Elshamy, Ahmed (2023) Intelligent solar panel monitoring system and shading detection using artificial neural networks. 2022 The 3rd International Conference on Power and Electrical Engineering, 9. pp. 324-334. https://doi.org/10.1016/j.egyr.2023.05.163
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
M. Abdallah, Fahad Saleh
Abdullah, M.N.
Musirin, Ismail
M. Elshamy, Ahmed
Intelligent solar panel monitoring system and shading detection using artificial neural networks
description 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.
format Article
author M. Abdallah, Fahad Saleh
Abdullah, M.N.
Musirin, Ismail
M. Elshamy, Ahmed
author_facet M. Abdallah, Fahad Saleh
Abdullah, M.N.
Musirin, Ismail
M. Elshamy, Ahmed
author_sort M. Abdallah, Fahad Saleh
title Intelligent solar panel monitoring system and shading detection using artificial neural networks
title_short Intelligent solar panel monitoring system and shading detection using artificial neural networks
title_full Intelligent solar panel monitoring system and shading detection using artificial neural networks
title_fullStr Intelligent solar panel monitoring system and shading detection using artificial neural networks
title_full_unstemmed Intelligent solar panel monitoring system and shading detection using artificial neural networks
title_sort intelligent solar panel monitoring system and shading detection using artificial neural networks
publisher Elsevier
publishDate 2023
url http://eprints.uthm.edu.my/9619/1/J16143_eac313c9cbc1fdd5c22b7e6ec3a3d051.pdf
http://eprints.uthm.edu.my/9619/
https://doi.org/10.1016/j.egyr.2023.05.163
_version_ 1775624946949554176
score 13.211869

Similar Items