Abstract
Transformer diagnosis and condition monitoring, literally a big deal for the utility professionals and is still posing a challenge to the researchers and domain experts of this area. It is clear that the accuracy of the diagnosis or maintenance process will more or less depend on the accuracy of the competence professional. Considering this as a constraint, lot of work has been done by eminent researchers using various artificial intelligence techniques like artificial neural networks, fuzzy logic and various algorithms for uplifting the accuracy of the diagnosis. Thus, a step ahead in this work, maintenance prioritization of power transformer has been carried out by using a Multiple Attribute Decision Making (MADM) technique, i.e., Analytical Hierarchy Process (AHP). Seven power transformers for which maintenance scheduling is to be done were considered as alternatives, and the results of various diagnostic tests such as furan analysis (2-FAL), total dissolved combustible gases (TDCG), Breakdown voltage (BDV), Dissipation Factor (DF), Acidity and Moisture content were considered as attributes for the corresponding transformer or alternative. Step-by-step calculations were done, and an optimal scheduling for these seven transformers was recommended considering the vulnerability state of insulation oil and criticality of the transformer.
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Acknowledgements
The authors are thankful to the authorities of TIFAC-CORE Centre of NIT Hamirpur (HP), India, for providing the necessary data for the transformers operating in Himachal Pradesh.
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Jain, K., Gupta, A., Sood, Y.R., Sharma, M. (2018). An Analytical Hierarchy Process Based Approach for Effective Maintenance Prioritization of Power Transformers. In: Singh, S., Wen, F., Jain, M. (eds) Advances in Energy and Power Systems. Lecture Notes in Electrical Engineering, vol 508. Springer, Singapore. https://doi.org/10.1007/978-981-13-0662-4_15
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DOI: https://doi.org/10.1007/978-981-13-0662-4_15
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