Smart grid-oriented oil-immersed transformer capacity estimation and early warning mechanism based on self-adapting forecasting model

A transformer is a pivotal component over the electrical power grid and provides a series of indispensable functions for the normal operation of the whole power system. Hence once even a transformer in a local substation goes abnormal, it will result in several chain reactions and eventually degrade the power quality and electricity service. Therefore, in the context of smart grid, transformer protection is still a significant and frequent topic. By utilizing the handy tool of information transfer provided by the smart grid, a novel transformer capacity estimation methodology can be established. In addition, its corresponding early warning mechanism based on oil-immersed transformer can also be constructed and provides an optimized protection.