RESEARCH ON THE TECHNOLOGY OF USING THERMOGRAPHY FOR DETECTING MALFUNCTIONS IN SOLAR PANELS
DOI:
https://doi.org/10.31891/2219-9365-2024-80-45Keywords:
thermography, solar panels, defects, infrared visualization, artificial intelligenceAbstract
In the proposed article, the use of thermography is examined as a highly effective method for detecting solar panel malfunctions, while also serving as a fundamental basis for monitoring and diagnostics in the field of solar energy. Local defects, such as overheating, cracks in photovoltaic cells, and disruptions of electrical connections, significantly reduce panel efficiency, causing energy losses. Thermography enables the swift and highly accurate identification of these issues by means of infrared visualization, thereby opening up innovative possibilities for enhancing overall system performance. The study provides a detailed analysis of various approaches to implementing thermographic methods, including the use of handheld thermal imagers, unmanned aerial vehicles equipped with thermal imaging cameras, and stationary monitoring systems. Special attention is devoted to integrating thermography with contemporary artificial intelligence algorithms, which facilitates the automated analysis of thermal images, the prediction of potential malfunctions, and the minimization of human error. The results of the research demonstrate that thermography may be regarded not only as a diagnostic tool but also as a promising instrument for managing the technical condition of panels. Its main advantages include rapid deployment, high accuracy, scalability, and integration with other modern technologies such as the “smart home” and the “Internet of Things.” At the same time, it is noted that high equipment costs and dependence on weather conditions remain key challenges for implementing this technology. The conclusions reached confirm the advisability of employing thermography to ensure the reliable operation of solar power plants and to reduce their environmental impact. Further technological progress, in particular with respect to artificial intelligence and unmanned aerial platforms, will support improvements in monitoring methods and boost the efficiency of renewable energy sources.
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Copyright (c) 2024 Андрій ЛИСИЙ, Віталій КІРЕТОВ
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