Abstract Digitalisation in the energy sector has opened up a wide range of different methodologies to analytically support the asset management process. Compared to previous periods, technology is better and more sophisticated, so there is better opportunity to actually know the condition of assets in the grid nowadays. All this is not feasible without a well-organised database with sufficient data about devices operation. While some assets in the transmission network have a whole group of sensors and measurement equipment which, with appropriate processing, can determine the condition or Asset Health Index of the assets quite accurately, on the other hand there are several devices with very low number or even without sensors whose condition we still want to know. Here numerous methodologies which use available historical data can be used. These can estimate the condition of devices over a given period and associated probability of their failure. This paper gives a practical example of implementation of methodology for analysing probability of failure, the survival curves of individual assets and the difficulties of integration with economic indicators in order to obtain risks. Derived methodology relies a large historical data set to provide results. The majority of data originates from the TSO technical and operational databases, so the resulting survival curves are based on real data, not the general approximations. Identified challenges related to database structures and the availability of appropriate data will also be outlined to enhance the data collection process.
Antončič et al. (Tue,) studied this question.