Transformer Health Monitoring Using Dissolved Gas Analysis: A Technical Brief

Cody Walker; Ahmad Al Rashdan; Vivek Agarwal

doi:10.36001/ijphm.2022.v13i2.3141

Transformer Health Monitoring Using Dissolved Gas Analysis A Technical Brief

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Published Jul 12, 2022

DOI https://doi.org/10.36001/ijphm.2022.v13i2.3141

Cody Walker

Idaho National Laboratory, Idaho Falls, ID, 83415, USA

Ahmad Al Rashdan

Idaho National Laboratory, Idaho Falls, ID, 83415, USA

Vivek Agarwal

Idaho National Laboratory, Idaho Falls, ID, 83415, USA

Abstract

As integral components of any power plant, transformers sup-ply the generated electricity to the grid. However, the trans-former’s cellulose-based paper insulation and the mineral oilin which it is immersed break down over time under stan-dard operating conditions—or more rapidly due to potentialfaults within the system. This technical brief exhibits a col-lection of diagnostic and prognostic techniques that utilitiescan adopted in lieu of labor-intense periodic preventive main-tenance routines. Furthermore, prognostic models have beenincorporated using the latest version of the Institute of Elec-trical and Electronics Engineers (IEEE) standard (IEEE StdC57.104TM-2019) for dissolved gas analysis (DGA), thusexpanding it to include estimation of the time to maintenance.Overall, four different methodologies are explained, each ofwhich aid in determining a transformer’s state of health. Thesemethodologies include the Chendong model, the IEEE C57.91-2011 thermal life consumption model, a diagnostic model forDGA, and a prognostic model for DGA that uses an autore-gressive integrated moving average (ARIMA) model. An ad-ditional improvement for estimating missing system parame-ters from monitoring data (i.e., a tool for parameter estimationutilizing Powell’s method) is presented, enabling the IEEEthermal life consumption model to benefit not only the col-laborating power plant, but also the power industry at large.

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References

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