Development of Intelligent Solar Panel Cleaning Robot for Enhanced Energy Efficiency

Tirth kumar Hitendrabhai Patel; Nisarg Nishith kumar Parekh; Sahil kumar Dineshbhai Parmar; Pritkumar Patel; Apexa Purohit; Mayur Chavda; Mayank Dev Singh; Jai Bahadur Balwanshi

doi:10.69968/664xsn65

Authors

Tirth kumar Hitendrabhai Patel UG Student, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Nisarg Nishith kumar Parekh UG Student, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Sahil kumar Dineshbhai Parmar UG Student, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Pritkumar Patel UG Student, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Apexa Purohit Assistant Professor, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Mayur Chavda Assistant Professor, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Mayank Dev Singh Associate Professor, Department of Mechatronics Engineering, ITM Vocational University, Vadodara, Gujarat, India
Jai Bahadur Balwanshi Dean, Faculty of Engineering & Technology, ITM Vocational University, Vadodara, Gujarat, India

DOI:

https://doi.org/10.69968/664xsn65

Keywords:

Autonomous Cleaning Robot, Photovoltaic Efficiency, Soiling Effect, ESP32 Microcontroller, Edge Detection, Renewable Energy, Levelized Cost of Energy (LCOE)

Abstract

A critical factor degrading solar panel efficiency is the soiling effect the accumulation of dust, particulate matter, bird droppings, and environmental debris on the anti-reflective coating of PV modules. Such optical obstruction significantly attenuates incident photon irradiance, leading to power generation losses of up to 30% in arid and semi-arid regions. Conventional manual cleaning interventions are labor-intensive, hazardous, and highly water-inefficient, highlighting the critical need for automated alternatives. This research presents the design, development, and validation of an intelligent, autonomous, and resource efficient robotic cleaning system tailored for inclined PV arrays. The proposed architecture utilizes a low-cost, high efficiency processing unit Arduino integrated with a customized wheeled chassis optimized for the tilt angles of standard PV installations. Navigation and spatial boundary recognition are governed by an advanced array of ultrasonic and infrared (IR) edge-detection sensors, ensuring strict adherence to the panel perimeter and preventing catastrophic falls. The electro-mechanical cleaning mechanism employs a continuous rotary brush coupled with a dry-wipe methodology, drastically reducing water consumption. Experimental validation conducted on a specialized test rig demonstrates robust edge detection under varying ambient light conditions and reliable locomotion on inclinations up to 25 degrees. Comparative analysis of current-voltage (I-V) characteristics before and after automated cleaning revealed a substantial recovery in PV power output, validating the system's efficacy. Ultimately, this autonomous robotic paradigm presents a scalable, cost-effective solution for large-scale solar farms, substantially improving the Levelized Cost of Energy (LCOE) while mitigating operational hazards and resource wastage.

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