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A Study on the Health Evaluation Method of Oil-immersed Transformer through Analysis of Insulating Oil

활선중 절연유 분석을 통한 유입변압기 건전성 평가 방법에 관한 연구

  • Youn-Jin Shin (Dept. of Safety and Environment Technology, Seoul National University of Science and Technology) ;
  • Jae-Yong Lim (Dept. of Safety and Environment Technology, Seoul National University of Science and Technology)
  • 신연진 (서울과학기술대학교 안전환경기술융합학과) ;
  • 임재용 (서울과학기술대학교 안전공학과)
  • Received : 2023.10.04
  • Accepted : 2023.11.22
  • Published : 2023.12.31

Abstract

The health state of the oil transformer is evaluated by the age of use and the state of internal defects. Mineral Oil, used as an insulator for oil transformers, creates specific gases and compounds through chemical reactions caused by heat, moisture, and partial discharge inside the transformer. It is possible to determine the aging and defect of the transformer through these gases and compounds. So, it is an important indicator to evaluate the health of a transformer. In this study, factors for assessing the health of transformers were hierarchically categorized, and key factors for each hierarchy were selected for design weighting. These weights were determined through surveys conducted with experts in the fields of transformer design, operation, and quality. For the health of a transformer, defect-related factors are approximately three times more important than factors related to aging. Additionally, defect-related factors showed a higher weighting for gases generated at high temperatures. Furthermore, Furan was determined to have a high weight, directly associated with insulating paper aging. Based on these findings, a health index was proposed, and a comparative analysis was conducted by categorizing 40 operational transformers into normal and comparison groups to evaluate and validate it.

Keywords

References

  1. S. H. Kim and T. S. Park, "Internal Defect Analysis of Transformers using DGA" j.inst. Korean. Electr. Electron. Eng., Vol. 24, No. 1, pp. 354-359, 2020.
  2. CIGRE WG 37.27, TB 176, Ageing of the System Impact on Planning, CIGRE, 2000.
  3. D. H. Kim, O. B. Lee and B. S. Ju, "KEPCO Substation Power Transformer Status and Fault Analysis" KIEE Summer Conference, pp. 912-0914, 2000.
  4. O. Y. Lee, H. S. Lee, S. S. Jeon, M. K. Jeong and H. K. Kang, "Lifetime Loss Calculation for Asset Management of a Power Transformer", The Transactions of the Korean Institute of Electrical Engineers Vol. 67P, No. 2, pp. 70-74, 2018.
  5. J. H. Chang, S. H. Lee and H. H. Lee, "A Study on Deterioration Evaluation Method by Condition Monitoring and Diagnosis for Aging Oil-immersed Power Transformers", The Transactions of the Korean Institute of Electrical Engineers, Vol. 63, No. 2, pp. 297-305, 2014. https://doi.org/10.5370/KIEE.2014.63.2.297
  6. A. Alqudsi and A. El-Hag, "Application of Machine Learning in Transformer Health Index Prediction" Energies, Vol. 12, Issue 14, p. 2694, 2019.
  7. A. Naderian, R. Piercy, S. Cress, F. Wang and J. Service, "An Approach to Determine the Health Index of Power Transformers" In: Conference Record of the 2008 IEEE International Symposium on Electrical Insulation, IEEE, pp. 192-196, 2008.
  8. R. A. Prasojo, A. Setiawan, Suwarno, N. U. Maulidevi and B. A.. Soedjarno, "Development of Analytic Hierarchy Process Technique in Determining Weighting Factor for Power Transformer Health Index" In: 2019 2nd International Conference on High Voltage Engineering and Power Systems (ICHVEPS), IEEE, pp. 1-5, 2019.
  9. R. A. Prasojo, Suwarno, N. U. Maulidevi and B. A. Soedjarno, "A Multiple Expert Consensus Model for Transformer Assessment Index Weighting Factor Determination" In: 2020 8th International Conference on Condition Monitoring and Diagnosis (CMD), IEEE, pp. 234-237, 2020.
  10. B. S. Kim, "A Study on the Detection of Outliers in Inflow Transformers Using Big Data", Department of Industrial & Systems Engineering Graduate School of Kongju National University Gong Ju, Korea, 2020.
  11. Q. T. Tran, L. Roose, B. D. Van and Q. N. Nguyen, "A Low-Cost Online Health Assessment System for Oil-Immersed Service Transformers Using Real-Time Grid Energy Monitoring" Energies, Vol. 15, Issue 16, p. 5932, 2022.
  12. S. Hernanda, A. C. Mulyana, D. A. Asfani, I. M. Y. Negara, D. Fahmi, "Application of Health Index Method for Transformer Condition Assessment", TENCON IEEE Region 10 Conference, IEEE, pp. 1-6, 2014.
  13. J. H. Sun, S. H. Yi and K. H. Kim, "Degradation Diagnosis of Insulation Paper Using CO and CO2 Gases in Oil Immersed Transformers", The Transaction of the Korean Institute of Electrical Engineers, Vol. 53C, Issue 10, pp. 523-529, 2004.
  14. G. B. Choi, S. Y. Eo, D. J. Kweon and D. J. Lee, "Diagnosis for the Transformer depend on Moisture and Furfural Detecting in Oil", Trans. KIEE, Vol 54C, No. 12, pp. 546-552, 2005.
  15. J. H. Kim and S. O. Han, "The Thermal Aging Characteristics of Cellulose Paper using Analysis for CO, CO2 Gas and Furan Compounds", The Transaction of the Korean Institute of Electrical Engineers, Vol. 58P, Issue 4, pp. 499-504, 2009.
  16. J. H. Lee, Y. G. Kim, J. W. Lee and J. H. Kim, "Risk Assessment of Mechanical Parking Facility during Construction based on AHP Analysis" J. Korean Soc. Saf., Vol. 37, No. 5, pp. 33-41, 2022.
  17. J. Y. Moon, "A Study on the Importance and Order of Priority of the Major Control Item for DMSMS by using AHP Analysis," Journal of the Korea Academia-Industrial Cooperation Society, Vol. 21, No. 10, pp. 48-54, 2020.
  18. J. H. Seong and Y. Byun, "A Study on the Weights of the Condition Evaluation of Rock Slope used in Entropy and AHP Method" J. Korean Soc. Saf., Vol. 31, No. 5, pp. 61-66, 2016. https://doi.org/10.14346/JKOSOS.2016.31.5.61
  19. IEC 60076-7, "Power Transformer-Part 7, : Loading Guide for Ooil-immersed Power Transformer", 2018.
  20. Y. Shang, L. Yang, Z. J. Guo and A. Yan, "Assessing aging of large transformers by FURFURAL Investication", IEEE, 272-274, 2001 Structural Importance and Fault Analysis", Journal of the Korean Institute of Illuminating and Electrical Installation Engineers, Vol. 27, Issue 4, pp. 23-30, 2013.  https://doi.org/10.5207/JIEIE.2013.27.4.023