Abstract
In order to make an optimal decision on a transformer during maintenance, relocation, loading and replacement, its insulation condition needs to be monitored and evaluated based on ageing stress levels and faults. In this paper, the usefulness of DP is explored for monitoring the condition of cellulose paper in a power transformer. The evaluation of the remaining life in an insulating paper is done by detection of dissolved gases such as carbon oxide gases and 2FAL compound in oil. The conventional method for obtaining DP is the direct method and actual paper samples are needed from the hotspot areas in the windings, which is quite costly and an intrusive process. So indirect methods are used by which DP and remaining life from furan concentration obtained from oil samples can be estimated and it is a non-costly and non-intrusive process. Here, application of two different techniques: mathematical models and fuzzy inference system (FIS) through which the DP value is evaluated. By means of mathematical models, DP can be estimated using the correlation between 2FAL and DP. Other technique uses the FIS model to determine the DP by considering 2FAL, CO2 and CO as inputs. Further, the best membership function that can give results with less deviation by comparing the obtained DP values from FIS model to experimental values was determined. Also, the values obtained from mathematical models are compared to those from FIS.
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Kanumuri, D., Sharma, V., Rahi, O.P. (2020). Remaining Life Assessment of Solid Insulation in Power Transformer Using Fuzzy Inference System (FIS). In: Singh Tomar, G., Chaudhari, N.S., Barbosa, J.L.V., Aghwariya, M.K. (eds) International Conference on Intelligent Computing and Smart Communication 2019. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0633-8_5
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