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Prognostics Health Management System for Power Transformer with IEC61850 and Internet of Things

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Abstract

Prognostic health management (PHM) plays an important role in electric systems, especially for power transformer. This paper focuses on two of five processes of PHM, which are sensing and analysis the parameter of the oil-immersed power transformer. The sensing process covers the selection of the sensors. In addition, the analysis process includes the health index (HI) evaluation and the prediction of the remaining useful life (RUL). The data flow in the PHM system started from the transformer’s sensors to the merging unit then to the engineering workstation through fiber optic cable. These data will be the inputs for the proposed fuzzy logic controller to evaluate the transformer’s overall health and indicated the HI. Furthermore, this data will be used to predict the RUL by the proposed equation that is based on the degree of polymerization of the insulation paper in the transformer oil. The PHM will be applied for the existing unit auxiliary transformer system in the advanced power reactor (APR1400) nuclear power plant, as a case study. The benefits of using this system are to improve reliability, increase the lifetime, predict the RUL of the transformer. In addition, it will reduce system monitoring errors, maintenance work, cost, and lessen unscheduled maintenance.

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Acknowledgements

This research was supported by the 2019 Research Fund of the KEPCO International Nuclear Graduate School (KINGS).

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Correspondence to Choong-Koo Chang.

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Cite this article

Elmashtoly, A.M., Chang, C. Prognostics Health Management System for Power Transformer with IEC61850 and Internet of Things. J. Electr. Eng. Technol. (2020). https://doi.org/10.1007/s42835-020-00366-0

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Keywords

  • Power transformer
  • Total dissolved combustible gases
  • Health index
  • IEC 61850-9-2
  • Prognostic health management
  • Remaining useful time
  • Fuzzy logic controller