Work

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

Year: 2025

Type: article

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.

Source: Renewable Energy

DOI: 10.1016/j.renene.2025.125084

Authors: B.M.A. Roshen Mendis, Jundika C. Kurnia, M.M. Reddy, S. Roy, S.M. Al-Ameri

Institutions: Curtin University Sarawak, Curtin University

Language: English

Topic: Photovoltaic System Optimization Techniques

Subfield: Renewable Energy, Sustainability and the Environment

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Climate action, Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,460