Comparison of Conventional and Fuzzy Logic Approach for DGA of EHV Transformer
Sachin G. Gaikwad1, P.S. Swami2, A. G.Thosar3
1Sachin G. Gaikwad, ME student, Department of Electrical Engineering, Government College of Engineering Aurangabad, Aurangabad, (Maharashtra), India.
2P.S. Swami, Department of Electrical Engineering, Government College of Engineering Aurangabad, Aurangabad, (Maharashtra), India.
3Dr. A. G. Thosar, H.O.D., Department of Electrical Engineering, Government College of Engineering Aurangabad, Aurangabad, (Maharashtra), India.
Manuscript received on 20 November 2015 | Revised Manuscript received on 30 November 2015 | Manuscript published on 30 November 2015 | PP: 30-37 | Volume-4 Issue-5, November 2015 | Retrieval Number: E1504114515©BEIESP
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Abstract: This paper deals with Dissolved gas analysis (DGA) of Extra High Voltage (EHV) transformers. Dissolved gas analysis (DGA) is a commonly used diagnostic testing tool which gives valuable information about fault developed inside the transformer. Development of incipient fault inside the transformer causes decomposition of oil and generation of combustible hydrocarbon gases. Amount and type of gas generated depends upon nature of fault in transformer.IEC and IEEE standards specify various techniques for interpretation of DGA test results. These conventional techniques include various ratio analysis methods. Many times these techniques fail to detect fault in transformer. This paper describes Fuzzy logic approach for interpretation of DGA test results. In this paper conventional and fuzzy logic method of DGA interpretation are implemented in MATLAB. DGA test data available for various EHV transformers is applied to fuzzy logic and conventional methods of DGA interpretation. Results obtained are compared with actual condition of transformer. Based on results obtained accuracy of fault detection for fuzzy logic method is calculated and compared with conventional interpretation methods
Keyword: DGA, Duval triangle, Fuzzy logic, IEC ratio..
Scope of the Article: Fuzzy logic