Solar Panel Cleaning Automatic Machine

Dust accumulation on solar panels significantly reduces their efficiency, leading to lower power output and financial losses. This research introduces an automated cleaning machine designed to remove dust and debris effectively. The system uses a rotating brush, a water spray mechanism, and automated controls powered by a microcontroller. The experimental setup involved testing solar panels exposed to environmental dust for five days, followed by cleaning with the machine. Post- cleaning results showed a noticeable increase in power output from 180W to 210W, with efficiency rising from 72% to 84%. Additionally, the system reduced water consumption by 30% compared to manual cleaning methods. The proposed solution offers a cost-effective, energy-efficient, and maintenance-friendly cleaning process. It is particularly suitable for large-scale solar farms where regular manual cleaning is impractical. The machine’s modular design allows for easy adaptation and future improvements, including IoT-based remote monitoring. This research demonstrates the potential of automated cleaning systems in maintaining solar panel performance, reducing operational costs, and promoting sustainable energy production

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-05
DOI
https://doi.org/10.5281/zenodo.17827934
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

Solar Panel Cleaning Automatic Machine

Zenodo (CERN European Organization for Nuclear Research)
Photovoltaic System Optimization Techniques
article

Solar Panel Cleaning Automatic Machine

article en

Abstract

Dust accumulation on solar panels significantly reduces their efficiency, leading to lower power output and financial losses. This research introduces an automated cleaning machine designed to remove dust and debris effectively. The system uses a rotating brush, a water spray mechanism, and automated controls powered by a microcontroller. The experimental setup involved testing solar panels exposed to environmental dust for five days, followed by cleaning with the machine. Post- cleaning results showed a noticeable increase in power output from 180W to 210W, with efficiency rising from 72% to 84%. Additionally, the system reduced water consumption by 30% compared to manual cleaning methods. The proposed solution offers a cost-effective, energy-efficient, and maintenance-friendly cleaning process. It is particularly suitable for large-scale solar farms where regular manual cleaning is impractical. The machine’s modular design allows for easy adaptation and future improvements, including IoT-based remote monitoring. This research demonstrates the potential of automated cleaning systems in maintaining solar panel performance, reducing operational costs, and promoting sustainable energy production

Zenodo (CERN European Organization for Nuclear Research)
Baba Farid University of Health Sciences (IN)
Responsible consumption and production
Openalex Percentile: Top 60%
Photovoltaic System Optimization Techniques
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