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Abstract <p>This study examines the evolution and advancement of solar cleaning robot technology, focusing on the development trajectory from the initial prototype to the most recent iteration. The context is set within the Middle East and North Africa (MENA) region, where the adoption of solar power initiatives is rapidly expanding. The need for efficient solar panel maintenance solutions is discussed, driven by dust and soiling accumulation challenges. The Sultanate of Oman’s ambitious renewable energy targets underscore the importance of innovative technologies like the Autonomous Solar Cleaning Robot (ASCR) in maintaining optimal photovoltaic (PV) system performance. It discusses the iterative design, functionality, and operational efficiency improvements, addressing challenges such as inaccurate brush contact and mechanical failures. The ASCR performance was tested through multiple testing and experimental conditions and was demonstrated by evaluating the solar system’s performance utilizing real-time data from irradiance, temperature, and dust sensors. The analysis performed revealed strong correlations between irradiance sensors and solar power production, with up to 100% correlation for both groups of panels. Additionally, a 90% correlation was found between the temperature readings and the power output data. The impact of dust and soiling on the solar system’s efficiency was also analyzed in this study, and a 30% energy reduction was recorded due to dust and soiling accumulation, which increasingly affects energy outcomes. Alongside the ASCR integration on the solar system, a DustIQ sensor was also integrated into the system to quantify the soiling ratios and identify the optimal cleaning interval, which, as a result, maximizes the ASCR efficiency. The findings from this study suggest that in order to ensure optimal solar panel efficiency is have an automated system responsive to real-time data generation, which helps manage dust and soiling accumulation and minimize downtime, thus ensuring more reliable renewable energy integration in the Oman region.</p>

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Prototype Optimization of Autonomous Solar Cleaning Robot

  • 期刊论文

  • 发表日期：

    2025年6月1日

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  • Hilal Al Hashmi,
  • Ibrahim Al Jassasi,
  • Ali Al Humairi,
  • Mohamed Al Salmi,
  • Yusuf Bulale,
  • Akrum Abdullatif,
  • Afzal Husain,
  • Peter Jung

摘要

Abstract

This study examines the evolution and advancement of solar cleaning robot technology, focusing on the development trajectory from the initial prototype to the most recent iteration. The context is set within the Middle East and North Africa (MENA) region, where the adoption of solar power initiatives is rapidly expanding. The need for efficient solar panel maintenance solutions is discussed, driven by dust and soiling accumulation challenges. The Sultanate of Oman’s ambitious renewable energy targets underscore the importance of innovative technologies like the Autonomous Solar Cleaning Robot (ASCR) in maintaining optimal photovoltaic (PV) system performance. It discusses the iterative design, functionality, and operational efficiency improvements, addressing challenges such as inaccurate brush contact and mechanical failures. The ASCR performance was tested through multiple testing and experimental conditions and was demonstrated by evaluating the solar system’s performance utilizing real-time data from irradiance, temperature, and dust sensors. The analysis performed revealed strong correlations between irradiance sensors and solar power production, with up to 100% correlation for both groups of panels. Additionally, a 90% correlation was found between the temperature readings and the power output data. The impact of dust and soiling on the solar system’s efficiency was also analyzed in this study, and a 30% energy reduction was recorded due to dust and soiling accumulation, which increasingly affects energy outcomes. Alongside the ASCR integration on the solar system, a DustIQ sensor was also integrated into the system to quantify the soiling ratios and identify the optimal cleaning interval, which, as a result, maximizes the ASCR efficiency. The findings from this study suggest that in order to ensure optimal solar panel efficiency is have an automated system responsive to real-time data generation, which helps manage dust and soiling accumulation and minimize downtime, thus ensuring more reliable renewable energy integration in the Oman region.