Proceedings of the Multimedia University Engineering Conference (MECON 2022)

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IoT-Based Monitoring System for Solar Photovoltaics’ Parameter Analysis and Prediction

Authors
Muhammad Afifuddin Pozi1, Heng Siong Lim1, Boon Kian Lim1, *, Kia Wai Liew1
1Faculty of Engineering and Technology, Multimedia University, Melaka, Malaysia
*Corresponding author. Email: bklim@mmu.edu.my
Corresponding Author
Boon Kian Lim
Available Online 23 December 2022.
DOI
10.2991/978-94-6463-082-4_35How to use a DOI?
Keywords
Solar PV monitoring system; Internet of Things (IoT); PV panel temperature; Support vector machine regression
Abstract

A popular alternative to using fossil fuels to generate power is to use a photovoltaic (PV) system. However, the efficiency of PV system is very sensitive to the environmental conditions and frequent maintenance is needed to achieve the best performance. In practice, data of both the surrounding environment and the PV system need to be collected simultaneously to monitor the status and also to characterize the performance of the system. But this cannot be done manually as the PV system is commonly placed at remote or hard-to-reach places. To address this problem, an IoT based solar photovoltaic monitoring system is designed and developed in this project. ESP32 is used as the core processing unit. Several sensors such as temperature, solar irradiation, current and voltage sensors are used for data collection. An IoT cloud server is used to store and display the data. The measurement results show satisfactory accuracy and reliability of the system. Further data analysis of the collected high temporal resolution sensor data reveals substantially different correlations of the parameters in three different weather conditions during non-rainy days, namely cool and cloudy, moderately hot and sunny, and very hot and sunny. A support vector machine (SVM) regression is proposed to predict the PV panel temperature and the result is compared to the conventional least square regression. Improved prediction performance is observed especially for the very hot and sunny scenario.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Multimedia University Engineering Conference (MECON 2022)
Series
Advances in Engineering Research
Publication Date
23 December 2022
ISBN
978-94-6463-082-4
ISSN
2352-5401
DOI
10.2991/978-94-6463-082-4_35How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Muhammad Afifuddin Pozi
AU  - Heng Siong Lim
AU  - Boon Kian Lim
AU  - Kia Wai Liew
PY  - 2022
DA  - 2022/12/23
TI  - IoT-Based Monitoring System for Solar Photovoltaics’ Parameter Analysis and Prediction
BT  - Proceedings of the Multimedia University Engineering Conference (MECON 2022)
PB  - Atlantis Press
SP  - 401
EP  - 412
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-082-4_35
DO  - 10.2991/978-94-6463-082-4_35
ID  - Pozi2022
ER  -