A validated online algorithm for detection of fan failures in oil-immersed power transformers

In this paper, a new online algorithm is proposed for detection of fan failures in power transformer based on the detection of changes in the estimated parameters of a thermal model; moreover, an allowed band is provided for triggering the alarm signal which is able to be applied on every oil-immersed transformer with AF cooling system. Furthermore, an empirical-based thermal model is proposed which uses different temperature-dependent thermal resistances corresponding to different heat transfer phenomena. Furthermore, the proposed algorithm is validated using the measured data of a 333 MVA ODAF and a 600 MVA OFAF power transformer including ambient temperature, load factor, number of operative pumps and fans, and top-oil temperature.