The master's thesis focuses on the implementation of periodic calculation of the Asset Health Index (AHI) for power transformers at the distribution system operator Elektro Gorenjska, d. d. The aim of the thesis is to implement a methodology for assessing the condition of transformers based on different parameters available at the time of writing. The calculation is presented based on temperature load, DGA analysis, furan in oil, moisture in oil, and age.
Using the Apache Superset software, a visualization of the results was created, allowing interactive monitoring and analysis of the data. The graphical user interface enables tracking the history of the AHI for each device and displaying the current state of power transformers in the distribution network.
In addition to the calculation and display of the AHI, the thesis explores various approaches to asset maintenance. Traditional approaches as well as advanced methods based on the condition of the device are presented. The thesis describes the needs and challenges encountered in implementing advanced maintenance. The master's thesis contributes to improving insight into the distribution network of Elektro Gorenjska, which is a key step towards the implementation of advanced maintenance methods. Accurate assessment of transformer conditions allows for better investment planning, reduces the risk of failures, and extends the apparent lifespan of the devices. The issue of AHI is not only present in the Slovenian electricity distribution but is a pressing problem worldwide. This master's thesis opens the door to further research and development in the field of smart maintenance of energy assets.
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