Operational state diagnosis algorithm of the oil-immersed transformer based on fuzzy synthetic evaluation model

The transformer is a pivotal device in substations, and its operational state is highly correlated to the security and reliability of a power system. Especially with the development of smart grid, the faults in transformers would have a severe negative impact, not only on the local power network, but also on the holistic power system and power grid. In this paper, we predominantly investigate the operating state diagnosis model of the oil-immersed transformer. Specifically, the common faults and their corresponding characteristics have been concluded. By the characterization of each fault, we can use the fuzzy synthetic evaluation model to diagnose whether a fault occurs and estimate its severity level as well as damage.