Title :
Application of gene expression programming (GEP) in power transformers fault diagnosis using DGA
Author :
Malik, Hasmat ; Mishra, Sukumar
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Technol. Delhi, New Delhi, India
Abstract :
The diagnosis of incipient fault is very important for power transformer condition monitoring. The incipient faults are monitored by conventional and artificial intelligence (AI) based models. In this paper, the GEP has been utilized to identify the incipient faults in an oil-immersed power transformer. Its performance is compared with traditional IEC/IEEE and AI methods (i.e. ANN and fuzzy logic). The juxtaposition of fault classification of ANN and FL method notify that proposed approach is much swiftly. The desired test analysis of experimental data from working transformers in the Northern Power Grid of India has been executed to present the robustness of evaluated incipient faults for wide changes in operational and loading conditions perturbations.
Keywords :
condition monitoring; evolutionary computation; fault diagnosis; power engineering computing; power transformers; ANN; DGA; FL method; GEP; Northern Power Grid of India; fault classification; fuzzy logic; gene expression programming; incipient faults; oil-immersed power transformer; power transformer condition monitoring; power transformers fault diagnosis; Accuracy; Artificial neural networks; Fault diagnosis; IEC standards; Oil insulation; Power transformer insulation; DGA; Power transformer; artificial intelligence; fault classification; gene expression programming (GEP);
Conference_Titel :
Power India International Conference (PIICON), 2014 6th IEEE
Print_ISBN :
978-1-4799-6041-5
DOI :
10.1109/34084POWERI.2014.7117782
