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Photovoltaic Cell Panels Soiling Inspection Using Principal Component Thermal Image Processing

A. Sriram1,*, T. D. Sudhakar2

1 Arasu Engineering College, Kumbakonam, Tamilnadu, 612501, India
2 St. Joseph’s College of Engineering, Chennai, Tamilnadu, 600119, India

* Corresponding Author: A. Sriram. Email: email

Computer Systems Science and Engineering 2023, 45(3), 2761-2772. https://doi.org/10.32604/csse.2023.028559

Abstract

Intended for good productivity and perfect operation of the solar power grid a failure-free system is required. Therefore, thermal image processing with the thermal camera is the latest non-invasive (without manual contact) type fault identification technique which may give good precision in all aspects. The soiling issue, which is major productivity affecting factor may import from several reasons such as dust on the wind, bird mucks, etc. The efficient power production sufferers due to accumulated soil deposits reaching from 1%–7% in the county, such as India, to more than 25% in middle-east countries country, such as Dubai, Kuwait, etc. This research offers a solar panel soiling detection system built on thermal imaging which powers the inspection method and mitigates the requirement for physical panel inspection in a large solar production place. Hence, in this method, solar panels can be verified by working without disturbing production operation and it will save time and price of recognition. India ranks 3rd worldwide in the usage use age of Photovoltaic (PV) panels now and it is supported about 8.6% of the Nation’s electricity need in the year 2020. In the meantime, the installed PV production areas in India are aged 4–5 years old. Hence the need for inspection and maintenance of installed PV is growing fast day by day. As a result, this research focuses on finding the soiling hotspot exactly of the working solar panels with the help of Principal Components Thermal Analysis (PCTA) on MATLAB Environment.

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Cite This Article

A. Sriram and T. D. Sudhakar, "Photovoltaic cell panels soiling inspection using principal component thermal image processing," Computer Systems Science and Engineering, vol. 45, no.3, pp. 2761–2772, 2023. https://doi.org/10.32604/csse.2023.028559



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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