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Machine Learning in Solar Plants Inspection Automation

Author

Listed:
  • Jacek Starzyński

    (Sense Software, Obrzeżna 1F/6U9, 02-691 Warszawa, Poland
    These authors contributed equally to this work.)

  • Paweł Zawadzki

    (Faculty of Electrical Engineering, Warsaw University of Technology, Koszykowa 75, 00-662 Warszawa, Poland
    These authors contributed equally to this work.)

  • Dariusz Harańczyk

    (SolarSoft, Sikorek 5, 43-300 Bielsko-Biała, Poland
    These authors contributed equally to this work.)

Abstract

The emergence of large photovoltaic farms poses a new challenge for quick and economic diagnostics of such installations. This article presents this issue starting from a quantitative analysis of the impact of panel defects, faulty installation, and lack of farm maintenance on electricity production. We propose a low-cost and efficient method for photovoltaic (PV) plant quality surveillance that combines technologies such as an unmanned aerial vehicle (UAV), thermal imaging, and machine learning so that systematic inspection of a PV farm can be performed frequently. Most emphasis is placed on using deep neural networks to analyze thermographic images. We show how the use of the YOLO network makes it possible to develop a tool that performs the analysis of the image material already during the flyby.

Suggested Citation

  • Jacek Starzyński & Paweł Zawadzki & Dariusz Harańczyk, 2022. "Machine Learning in Solar Plants Inspection Automation," Energies, MDPI, vol. 15(16), pages 1-21, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:16:p:5966-:d:890912
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    References listed on IDEAS

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    1. Joshuva Arockia Dhanraj & Ali Mostafaeipour & Karthikeyan Velmurugan & Kuaanan Techato & Prem Kumar Chaurasiya & Jenoris Muthiya Solomon & Anitha Gopalan & Khamphe Phoungthong, 2021. "An Effective Evaluation on Fault Detection in Solar Panels," Energies, MDPI, vol. 14(22), pages 1-14, November.
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    Cited by:

    1. Abdullah Ahmed Al-Dulaimi & Muhammet Tahir Guneser & Alaa Ali Hameed & Fausto Pedro García Márquez & Norma Latif Fitriyani & Muhammad Syafrudin, 2023. "Performance Analysis of Classification and Detection for PV Panel Motion Blur Images Based on Deblurring and Deep Learning Techniques," Sustainability, MDPI, vol. 15(2), pages 1-32, January.
    2. Kyoik Choi & Jangwon Suh, 2023. "Fault Detection and Power Loss Assessment for Rooftop Photovoltaics Installed in a University Campus, by Use of UAV-Based Infrared Thermography," Energies, MDPI, vol. 16(11), pages 1-16, June.
    3. Elias Roumpakias & Tassos Stamatelos, 2023. "Comparative Performance Analysis of a Grid-Connected Photovoltaic Plant in Central Greece after Several Years of Operation Using Neural Networks," Sustainability, MDPI, vol. 15(10), pages 1-26, May.

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