Smart Solar Photovoltaic Panel Dust Monitoring System Using Internet of Thing (IoT)

Photovoltaic technology has become one of the most popular ways of generating power from renewable energy sources. Solar panels are solely responsible for generating the maximum amount of electricity. One of the reasons to be rectified is the lack of equipment or systematic monitoring of solar panels. Due to their surface being covered with dust and not being cleaned for a long time, solar panels can get damaged and become unable to generate electricity. This project investigates the factors of dust that impact photovoltaic module performance and designs an intelligent monitoring system. The project aims to develop a monitoring system that allows users to use their smartphones to monitor the cleanliness of solar panels. This monitoring kit includes a dust sensor component as data input and a NodeMCU ESP32 microcontroller that receives, processes, and sends data to the Blynk application. The project enables the owners to monitor their solar panels in real-time. The results show that solar panel performance has decreased by 61% when the reading value of dust sensor 1 is 47%, dust sensor 2 is 30%, dust sensor 3 is 53%, and dust sensor 4 is 50%. The benefits of this project are that solar panel maintenance will be more systematic, ensuring solar panels can generate the maximum electricity, and they are not easily damaged, thus increasing the lifespan of solar panels.

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Publication Details

Journal
Journal of Advanced Research in Applied Mechanics
Published
2024-08-30
DOI
https://doi.org/10.37934/aram.123.1.1530
Citations
2
Primary Topic
IoT-based Smart Home Systems
Type
article
Field-Weighted Citation Impact
0.42

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article

Smart Solar Photovoltaic Panel Dust Monitoring System Using Internet of Thing (IoT)

Nor Aira Zambri, Norhafiz Salim, Farahiyah Mustafa, Sim Sy Yi et al.
2 citations
Journal of Advanced Research in Applied Mechanics
IoT-based Smart Home Systems
0.42
article

Smart Solar Photovoltaic Panel Dust Monitoring System Using Internet of Thing (IoT)

Nor Aira Zambri, Norhafiz Salim, Farahiyah Mustafa, Sim Sy Yi, Omar Abu Hassan, Mohd Nasri Jasmie, Siti Nur Afifah Mohd Suhaimi
article en
2 citations

Abstract

Photovoltaic technology has become one of the most popular ways of generating power from renewable energy sources. Solar panels are solely responsible for generating the maximum amount of electricity. One of the reasons to be rectified is the lack of equipment or systematic monitoring of solar panels. Due to their surface being covered with dust and not being cleaned for a long time, solar panels can get damaged and become unable to generate electricity. This project investigates the factors of dust that impact photovoltaic module performance and designs an intelligent monitoring system. The project aims to develop a monitoring system that allows users to use their smartphones to monitor the cleanliness of solar panels. This monitoring kit includes a dust sensor component as data input and a NodeMCU ESP32 microcontroller that receives, processes, and sends data to the Blynk application. The project enables the owners to monitor their solar panels in real-time. The results show that solar panel performance has decreased by 61% when the reading value of dust sensor 1 is 47%, dust sensor 2 is 30%, dust sensor 3 is 53%, and dust sensor 4 is 50%. The benefits of this project are that solar panel maintenance will be more systematic, ensuring solar panels can generate the maximum electricity, and they are not easily damaged, thus increasing the lifespan of solar panels.

Journal of Advanced Research in Applied MechanicsVol. 123(1)
Technical University of Malaysia Malacca (MY), Tun Hussein Onn University of Malaysia (MY)
Universiti Tun Hussein Onn Malaysia
Affordable and clean energy
Openalex Percentile: Top 38%
IoT-based Smart Home Systems
0.42
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Smart Solar Photovoltaic Panel Dust Monitoring System Using Internet of Thing (IoT) — Nor Aira Zambri, Norhafiz Salim, et al. · Journal of Advanced Research in Applied Mechanics (2024) | TGRS Research Map | TGRS