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<p>Photovoltaic technology is essential for generating clean electricity directly from solar radiation. In addition, it absorbs substantial heat, which can be harnessed for thermal applications in hybrid photovoltaic thermal systems. Therefore, this study systematically reviews recent PV panel optimization innovations, specifically focusing on industrial and automated technologies such as solar tracking systems, robotic cleaning units, and condition monitoring tools. This work evaluates industrial automation’s impact on PV panel performance, manufacturing efficiency, and system reliability. The methodology of inclusion criteria prioritized peer-reviewed articles (2017–2025) and experimental studies with quantitatively reported outcomes and visual documentation. Quantitative data indicate that automated systems can reduce human-induced errors by up to 90% and increase production rates by a factor of 3 to 5 compared to manual processes. Furthermore, key findings demonstrate that while automated tracking systems can increase energy yield by 25–45% and robotic cleaners can improve efficiency by 11–28%, their economic feasibility depends on local conditions and the scale of deployment. The presented review offers a roadmap for future research and design of hybrid, intelligent solar panel systems by identifying current limitations and proposing targeted solutions.</p> Graphical abstract <p></p>

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The role of automated technologies and industrial mechanisms in upgrading photovoltaic panel performance

  • 期刊论文

  • 发表日期：

    2025年7月3日

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  • Abdulrahman Al-Omari,
  • Amr Elbrashy,
  • Abdelrahman T. Elgohr,
  • Marwa El-Geneedy,
  • Shimaa Akram,
  • Mohamed S. Elhadidy

摘要

Photovoltaic technology is essential for generating clean electricity directly from solar radiation. In addition, it absorbs substantial heat, which can be harnessed for thermal applications in hybrid photovoltaic thermal systems. Therefore, this study systematically reviews recent PV panel optimization innovations, specifically focusing on industrial and automated technologies such as solar tracking systems, robotic cleaning units, and condition monitoring tools. This work evaluates industrial automation’s impact on PV panel performance, manufacturing efficiency, and system reliability. The methodology of inclusion criteria prioritized peer-reviewed articles (2017–2025) and experimental studies with quantitatively reported outcomes and visual documentation. Quantitative data indicate that automated systems can reduce human-induced errors by up to 90% and increase production rates by a factor of 3 to 5 compared to manual processes. Furthermore, key findings demonstrate that while automated tracking systems can increase energy yield by 25–45% and robotic cleaners can improve efficiency by 11–28%, their economic feasibility depends on local conditions and the scale of deployment. The presented review offers a roadmap for future research and design of hybrid, intelligent solar panel systems by identifying current limitations and proposing targeted solutions.

Graphical abstract