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Dissolved Gas Analysis in Power Transformer using Artificial Neural Network

Publication Date : 02/05/2016

Author(s) :

Bankar Rahul Sanjay , Prof..P.A.Desai .

Conference Name :
International Conference on Recent Trends in Engineering and Technology

Abstract :

Power transformers plays most crucial in power system. It transfers of power from one voltage level to another. Power transformer breakdown or damage may interrupt power transmission & distribution operation Under continuous operation confront to the electrical and thermal stresses. Fault in the power transformer may lead to the power supply interruption The Dissolved Gas Analysis to detect incipient faults has been improved using artificial neural networks and is compared with Rogers ratio method with available samples of field information. Dissolved gas analysis (DGA) is a reliable technique for detecting the presence of incipient fault conditions in oil immersed transformers. In this method the presence of certain key gases is monitored. The various analysis methods are : Rogers ratio, IEC ratio, Doernenburg, Duval triangle, key gas, artificial neural network (ANN) method. In this paper the various DGA methods are evaluated and compared. The key gases considered are hydrogen, methane, ethane, ethylene, acetylene.

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