Performance Test of Power Transformer Prior to Maintenance using DGA and Grey Relational Analysis
Vikal R. Ingle1, V. T. Ingole2
1Professor. Vikal R. Ingle, Department of Electronics, B. D. College of Engineering, Sevagram, District. Wardha (MS), India.
2Dr. V. T. Ingole, Professor. Ram Meghe Institute Technology & Research, Badnera, Amravati, India.
Manuscript received on February 22, 2015. | Revised Manuscript received on February 27, 2015. | Manuscript published on March 05, 2015. | PP: 48-51 | Volume-5 Issue-1, March 2015. | Retrieval Number: F2489014615/2015©BEIESP
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©The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/
Abstract: The insulation of power transformer i.e. oil and paper decomposition recognized by means of dissolved gas-in-oil analysis (DGA). To detect incipient faults in a transformer, standard key gas method of DGA is employed on the basis of quantity of gases released from the oil. This primary information also reflects the overall condition of a transformer. In this paper, condition assessment of power transformer using relative scaling is discussed. Grey relational analysis is identified as best option for relative scaling, wherein the data of fleet connected transformers is compared and accordingly scales them on the strength of score. Grey relational analysis on key gas sample determines the Target Heart Degrees (THD) of a specific transformer. However, THD represent the average estimation of bull’s eye coefficients, calculated by means of attributes with equal weight condition. Subsections linearity relations are utilized to decide seven intervals for ranking purpose. Linear regression demonstrated on subsection linearity relations for different sets of key gas samples. Result shows the dominance of proposed model in deciding the maintenance priorities.
Keywords: DGA, Key gas method, Grey Relational Analysis, Target Heart Degree, Rank Approaching Degree, subsections linearity relation.