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Research Article
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Regional Guidance System for Cleaning Robots as a Result of Pollution of Solar Panels

Year 2023, Volume: 22, 274 - 279, 01.09.2023

Emin Cantez Hasan Sahın Omer Faruk Efe

https://doi.org/10.55549/epstem.1350961

Abstract

Solar energy production is provided by thermal and photovoltaic (PV) systems. Among them, PVs are considered one of the most important power generation systems that produce safe and sustainable energy. Depending on the outdoor conditions, PV systems get dirty over time due to dust, rain and environmental factors. Above the PV system When polluted, it causes a significant decrease in their efficiency. Especially in large photovoltaic power plants, it is seen that the panels are not polluted equally. But the cleaning robots system When it starts to clean, it cleans all the panels. Cleaning all clean and dirty panels causes energy consumption, material life and spare parts waste. In the system we have planned, it is planned to clean the panels by detecting the dirty panels with the camera and directing the cleaning robot only to the contaminated areas. Since only the contaminated areas will be cleaned, the energy production efficiency of the panels will increase and the cleaning time will be shortened.

Keywords

Photovoltaic Energy Image processing Object detection Camera

References

  • Acikgoz H. (2022).A novel approach based on integration of convolutional neural networks and deep feature selection for short-term solar radiation forecasting. Appl Energy,305. 117912..
  • Ali, M.U., Khan, H.F., Masud M., Kallu K.D., & Zafar, A. (2020) A machine learning framework to identify the hotspot in photovoltaic module using infrared thermography. Solar Energy, 208,643–651.
  • Amidi, A., Amidi, S., Vlachakis, D., Paragios, N., & Zacharaki, EI. (2016) A machine learning methodology for enzyme functional classification combining structural and protein sequence descriptors. Lecture Notes in Computer Science, 9656, 728–738.

Year 2023, Volume: 22, 274 - 279, 01.09.2023

Emin Cantez Hasan Sahın Omer Faruk Efe

https://doi.org/10.55549/epstem.1350961

Abstract

References

  • Acikgoz H. (2022).A novel approach based on integration of convolutional neural networks and deep feature selection for short-term solar radiation forecasting. Appl Energy,305. 117912..
  • Ali, M.U., Khan, H.F., Masud M., Kallu K.D., & Zafar, A. (2020) A machine learning framework to identify the hotspot in photovoltaic module using infrared thermography. Solar Energy, 208,643–651.
  • Amidi, A., Amidi, S., Vlachakis, D., Paragios, N., & Zacharaki, EI. (2016) A machine learning methodology for enzyme functional classification combining structural and protein sequence descriptors. Lecture Notes in Computer Science, 9656, 728–738.
There are 3 citations in total.

Details

Primary Language English
Subjects Photovoltaic Power Systems
Journal Section Articles
Authors

Emin Cantez

Hasan Sahın

Omer Faruk Efe

Early Pub Date August 27, 2023
Publication Date September 1, 2023
Published in Issue Year 2023 Volume: 22

Cite

APA Cantez, E., Sahın, H., & Efe, O. F. (2023). Regional Guidance System for Cleaning Robots as a Result of Pollution of Solar Panels. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 22, 274-279. https://doi.org/10.55549/epstem.1350961
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