Dual-axis solar tracking system with real-time weather-responsive self-cleaning mechanism for photovoltaic panels

One of the key challenges in the adoption of solar PV is maintaining clean panel surfaces as accumulation of dirt and dust will deteriorate the solar PV performance. Consequently, various cleaning technologies for the solar PV have been developed ranging from manual to active mechanical cleaning. The former is labour and water intensive while the latter requires additional components and power, increasing system complexity. An intriguing option is to utilize existing component such as the solar tracking system, enabling its potential as an autonomous cleaning system. However, to date, no study exploring this scenario has been reported. This study proposes and evaluates a novel self-cleaning approach for solar PV panels by integrating an adaptive cleaning mechanism into a dual-axis solar tracker system. Unlike commonly adopted cleaning systems that require water, brushes, wipers or other cleaning tools, this adaptive cleaning mechanism utilizes real-time detection of rainfall, wind speed, and direction to activate an autonomous tilting sequence. This dynamic repositioning harnesses natural forces (specifically rainwater and wind) to dislodge surface debris without physical contact or additional energy input. Three systems are evaluated: ( i ) the proposed dual-axis solar tracker with integrated weather-responsive self-cleaning, ( ii ) a basic dual-axis solar tracker without the cleaning mechanism, and ( iii ) a fixed-angle system, used as a benchmark. Initial performance evaluation based on visual inspection and power output measurements indicate that high wind speeds and heavy rainfall are crucial in achieving optimal self-cleaning. To improve performance under low-wind conditions, an enhanced mechanism was introduced, resulting in more consistent cleaning across varied weather scenarios. These findings demonstrate the potential of integrating adaptive self-cleaning strategies with solar tracking technology to enhance PV panel efficiency and durability.

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Publication Details

Journal
Renewable Energy
Published
2025-12-20
DOI
https://doi.org/10.1016/j.renene.2025.125084
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
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article

Dual-axis solar tracking system with real-time weather-responsive self-cleaning mechanism for photovoltaic panels

Shaima AlAmeri, Jundika C. Kurnia, Sukanta Roy, Budhika G. Mendis et al.
Renewable Energy
Photovoltaic System Optimization Techniques
article

Dual-axis solar tracking system with real-time weather-responsive self-cleaning mechanism for photovoltaic panels

Shaima AlAmeri, Jundika C. Kurnia, Sukanta Roy, Budhika G. Mendis, Michael M. Reddy
article en

Abstract

One of the key challenges in the adoption of solar PV is maintaining clean panel surfaces as accumulation of dirt and dust will deteriorate the solar PV performance. Consequently, various cleaning technologies for the solar PV have been developed ranging from manual to active mechanical cleaning. The former is labour and water intensive while the latter requires additional components and power, increasing system complexity. An intriguing option is to utilize existing component such as the solar tracking system, enabling its potential as an autonomous cleaning system. However, to date, no study exploring this scenario has been reported. This study proposes and evaluates a novel self-cleaning approach for solar PV panels by integrating an adaptive cleaning mechanism into a dual-axis solar tracker system. Unlike commonly adopted cleaning systems that require water, brushes, wipers or other cleaning tools, this adaptive cleaning mechanism utilizes real-time detection of rainfall, wind speed, and direction to activate an autonomous tilting sequence. This dynamic repositioning harnesses natural forces (specifically rainwater and wind) to dislodge surface debris without physical contact or additional energy input. Three systems are evaluated: ( i ) the proposed dual-axis solar tracker with integrated weather-responsive self-cleaning, ( ii ) a basic dual-axis solar tracker without the cleaning mechanism, and ( iii ) a fixed-angle system, used as a benchmark. Initial performance evaluation based on visual inspection and power output measurements indicate that high wind speeds and heavy rainfall are crucial in achieving optimal self-cleaning. To improve performance under low-wind conditions, an enhanced mechanism was introduced, resulting in more consistent cleaning across varied weather scenarios. These findings demonstrate the potential of integrating adaptive self-cleaning strategies with solar tracking technology to enhance PV panel efficiency and durability.

Renewable EnergyVol. 259
Curtin University Sarawak (MY), Maulana Azad National Institute of Technology (IN)
Openalex Percentile: Top 69%
Photovoltaic System Optimization Techniques
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