Transformer faults identification via fuzzy logic approach

The need for a constant electricity supply is at an alarming rate especially in the 21st century due to the high rate of increase in industrialization across the globe. Conventional protection schemes such as differential relays, Buchholz relay, and other techniques such as genetic algorithms and artificial neural networks, do not match the precision and reliability needed for transformer fault indentification, due to their complexity in computation, tedious training system, time consumption, and need the of human experts. The method proposed in this research is the use of a fuzzy inference system in detecting potential faults in power system transformers. The faults in the transformer were observed and analyzed using a simulation system of MATLAB/Simulink software. The suggested approach ensures swift identification of faults as it relies on if-then rules and only uses current and voltage measurements with 100% independence toward the power flow direction, making it highly reliable and simple to implement compared to other techniques for transformer fault identification.