Assessing Damage to Solar Farm using Photographs and Thermal Image from Unmanned Aerial Vehicles

Authors

  • Palakorn Prommet Associate Professor, Department of Electrical Engineering, Faculty of Engineering, Princess of Naradhiwas University, Narathiwat 96000, Thailand

DOI:

https://doi.org/10.55164/jgrdi.v1i2.2206

Keywords:

Thermal Image, Solar Panel, Unmanned Aerial Vehicles, Preventive Maintenance

Abstract

This research presented the assessment of solar panel damage using photographic and thermal images from unmanned aerial vehicles (UAV) in the area of a ground-based solar power generation project or solar farm with a maximum production capacity of 502.2 kWp in the area of the President's Office, Princess of Naradhiwas University. The objectives were to assess the environment, dirtiness, overall and individual damage to the panels, and deterioration of the solar modules inside the panels, which were caused by the installation and use throughout the 5 - year period of the project.  The survey flights could classify the damage to the solar panels in the project, such as cracks in the solar panel windshield, environment dirtiness from the solar panel, shading from weeds on the solar panels, internal corrosion (rusting) and peeling, and the occurrence of hot spots inside the solar panels, etc. The use of UAV could help save time and costs in surveying and inspection operations in the case of large-scale projects. In addition, the results of the survey could be used to plan preventive maintenance correctly and appropriately in the future.

References

Subcommittee on Consideration of Laws, Structures, Duties and Powers of Agencies Related to Information Technology. (2020). Report on the Study on Guidelines for Promoting the Use of Commercial Unmanned Aircraft Technology. Senate Committee on Information, Communication and Telecommunications Technology Meeting No. 26/2020, 18 August 2020.

Narcotic Plant Survey and Monitoring Institute. (2017, February 17). Knowledge organization on unmanned aerial vehicles for narcotic plant survey. Office of the Narcotics Control Board: Ministry of Justice. http://www.oncb.go.th/ncsmi/doc3/อากาศยานไรคนขับเพื่อการสำรวจพืชเสพติด.pdf

Prommet, P., & Palasai, W. (2023). Study of predictive maintenance of wind turbines at Lam Takhong Chala Pha Wattana Power Plant, Nakhon Ratchasima Province using a group unmanned aerial vehicle combined with an artificial intelligence processing system. Electricity Generating Authority of Thailand.

Ferrara, C., & Philipp, D. (2012). Why do PV modules fail?, Energy Procedia, 15, 379-387. https://doi.org/10.1016/j.egypro.2012.02.046

Köntges, M., Kurtz, S.R., Packard, C.E., Jahn, U., Berger, K.A., Kato, K., Friesen, T., Liu, H., Iseghem, M.V., Wohlgemuth, J.H., Miller, D.C., Kempe, M.D., Hacke, P., Reil, F., Bogdanski, N., Herrmann, W., Buerhop‐Lutz, C., Razongles, G., & Friesen, G. (2014). Review of Failures of Photovoltaic Modules. Report IEA-PVPS T13-01:2014, International Energy Agency (IEA). http://iea-pvps.org/wp-content/uploads/2020/01/IEA-PVPS_T13-01_2014_Review_of_Failures_of_Photovoltaic_Modules_Final.pdf

Zou, J. -T. & Rajveer, G. V. (2022). Drone-based solar panel inspection with 5G and AI Technologies. 2022 8th International Conference on Applied System Innovation (ICASI), Nantou, Taiwan, 2022, 174-178. https://doi.org/10.1109/ICASI55125.2022.9774462

Pruthviraj, U., Kashyap, Y., Baxevanaki, E. & Kosmopoulos, P. (2023). Solar photovoltaic hotspot inspection using unmanned aerial vehicle thermal images at a solar field in South India. Remote Sensing. 15(7), 1914. https://doi.org/10.3390/rs15071914

Masita, K., Hasan, A., & Shongwe, T. (2022). 75MW AC PV module field anomaly detection using drone-based IR orthogonal images with Res-CNN3 detector. IEEE Access, 10, 83711-83722. https://doi.org/10.1109/ACCESS.2022.3194547

DJI Bangkok. (2021). DJI Mavic 2 Enterprise Advanced. https://www.djibangkok.com/shop/dji-mavic-2-enterprise-advanced

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Published

03/13/2025

How to Cite

Prommet, P. (2025). Assessing Damage to Solar Farm using Photographs and Thermal Image from Unmanned Aerial Vehicles. Journal of Graduate Research Development and Innovation, 1(2), 29–36. https://doi.org/10.55164/jgrdi.v1i2.2206

Issue

Section

Research Articles