The aim of my dissertation is to provide a comprehensive picture about dynamic line rating technology (DLR) and icing of power lines. Furthermore, the development of a system is shown, that can provide feedback on icing and snow deposits at each stage, supported by artificial intelligence. This major motivation was that, based on this information, system operators can prevent the occurrence of damage by applying dynamic load.
In my thesis, I introduce the theoretical basis of the dynamic line rating. Examine the initial factors and consider the limits of thermal load.
I think it is important to look at the research and results of foreign development companies that are active in this field today.
Reading the case studies, it became clear to me that the most up-to-date IT technologies should be used for modern solutions. This is currently the Internet of Things, machine learning, augmented reality and artificial intelligence.
During my dissertation, I tried to show through examples the processes of icing of the transmission lines, the precipitation, and the inherent risks to the transmission system.
Then I create a comprehensive picture about artificial intelligence. Then I presented some of the solutions already used in the energy industry.
Finally, I developed my own model. With the help of Custom Vision, I created an interface for demonstrating the functionality of an intelligent system, where I can show how it would work in practice on a drone, on a device installed on a wire, or on a system operator centre.