Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Autoren

  • Tobias Kinkeldey
  • Tobias Münster
  • Peter Werle
  • Suwarno
  • Kai Hämel
  • Jörg Preusel

Externe Organisationen

  • Institut Teknologi Bandung (ITB)
  • GRIDINSPECT GmbH
Forschungs-netzwerk anzeigen

Details

OriginalspracheEnglisch
Titel des SammelwerksProceedings of the 21st International Symposium on High Voltage Engineering - Volume 1
Herausgeber (Verlag)Springer Nature
Seiten926-936
Seitenumfang11
ISBN (elektronisch)978-3-030-31676-1
ISBN (Print)9783030316754
PublikationsstatusVeröffentlicht - 2020
Veranstaltung21st International Symposium on High Voltage Engineering, ISH 2019 - Budapest, Ungarn
Dauer: 26 Aug. 201930 Aug. 2019

Publikationsreihe

NameLecture Notes in Electrical Engineering
Band598 LNEE
ISSN (Print)1876-1100
ISSN (elektronisch)1876-1119

Abstract

The condition of the transformer insulation determines the remaining life of the transformer. Over the transformer service life, both liquid and solid insulation undergoes a continuous aging process under electrical, chemical, mechanical and thermal stresses. The insulating liquid of a transformer can be reconditioned or replaced; however, this is not the case for the cellulose insulation. Therefore, the condition of the paper insulation is the major factor for determining the aging status of a transformer. To assess the paper condition, the common method is to measure the degree of polymerization (DP) of the paper insulation as a significant parameter. This method is destructive as it requires a sample of paper from inside of the transformer. Therefore, it could not be applied for transformers in operation. There are several approaches to approximate the DP value without direct measurements of paper samples. This research presents an improved method based on a fuzzy logic system for the estimation of the DP based on dissolved gases and chemical parameters of the liquid insulation. The algorithm is developed to create the rules for the use of fuzzy sets based on the information gain extracted by the entropy of the laboratory measurement data. This algorithm employs entropy to examine the sample homogeneity. Entropy is a measure of information theory that can determine the dataset characteristics concerning impurity and homogeneity. The algorithm uses fuzzy sets of oil parameters like Acidity, Interfacial Tension (IFT), Carbon Dioxide (CO2) and Carbon Monoxide (CO) and the breakdown voltage (BDV) for determination of the DP value.

ASJC Scopus Sachgebiete

Zitieren

Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm. / Kinkeldey, Tobias; Münster, Tobias; Werle, Peter et al.
Proceedings of the 21st International Symposium on High Voltage Engineering - Volume 1. Springer Nature, 2020. S. 926-936 (Lecture Notes in Electrical Engineering; Band 598 LNEE).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Kinkeldey, T, Münster, T, Werle, P, Suwarno, Hämel, K & Preusel, J 2020, Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm. in Proceedings of the 21st International Symposium on High Voltage Engineering - Volume 1. Lecture Notes in Electrical Engineering, Bd. 598 LNEE, Springer Nature, S. 926-936, 21st International Symposium on High Voltage Engineering, ISH 2019, Budapest, Ungarn, 26 Aug. 2019. https://doi.org/10.1007/978-3-030-31676-1_87
Kinkeldey, T., Münster, T., Werle, P., Suwarno, Hämel, K., & Preusel, J. (2020). Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm. In Proceedings of the 21st International Symposium on High Voltage Engineering - Volume 1 (S. 926-936). (Lecture Notes in Electrical Engineering; Band 598 LNEE). Springer Nature. https://doi.org/10.1007/978-3-030-31676-1_87
Kinkeldey T, Münster T, Werle P, Suwarno, Hämel K, Preusel J. Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm. in Proceedings of the 21st International Symposium on High Voltage Engineering - Volume 1. Springer Nature. 2020. S. 926-936. (Lecture Notes in Electrical Engineering). Epub 2019 Nov 28. doi: 10.1007/978-3-030-31676-1_87
Kinkeldey, Tobias ; Münster, Tobias ; Werle, Peter et al. / Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm. Proceedings of the 21st International Symposium on High Voltage Engineering - Volume 1. Springer Nature, 2020. S. 926-936 (Lecture Notes in Electrical Engineering).
Download
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title = "Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel Fuzzy Logic Algorithm",
abstract = "The condition of the transformer insulation determines the remaining life of the transformer. Over the transformer service life, both liquid and solid insulation undergoes a continuous aging process under electrical, chemical, mechanical and thermal stresses. The insulating liquid of a transformer can be reconditioned or replaced; however, this is not the case for the cellulose insulation. Therefore, the condition of the paper insulation is the major factor for determining the aging status of a transformer. To assess the paper condition, the common method is to measure the degree of polymerization (DP) of the paper insulation as a significant parameter. This method is destructive as it requires a sample of paper from inside of the transformer. Therefore, it could not be applied for transformers in operation. There are several approaches to approximate the DP value without direct measurements of paper samples. This research presents an improved method based on a fuzzy logic system for the estimation of the DP based on dissolved gases and chemical parameters of the liquid insulation. The algorithm is developed to create the rules for the use of fuzzy sets based on the information gain extracted by the entropy of the laboratory measurement data. This algorithm employs entropy to examine the sample homogeneity. Entropy is a measure of information theory that can determine the dataset characteristics concerning impurity and homogeneity. The algorithm uses fuzzy sets of oil parameters like Acidity, Interfacial Tension (IFT), Carbon Dioxide (CO2) and Carbon Monoxide (CO) and the breakdown voltage (BDV) for determination of the DP value.",
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note = "Funding information: Acknowledgments. The authors would like to express their graduate to GRIDINSPECT GmbH and AiF/ZiM for the financial support as well as Weidmann Electrical Technology AG for the support with insulation materials and Analysen Service GmbH Leipzig for the analysis. Furthermore, the authors would like to thank the company ABB for the provision of comparative data. The authors would like to express their graduate to GRIDINSPECT GmbH and AiF/ZiM for the financial support as well as Weidmann Electrical Technology AG for the support with insulation materials and Analysen Service GmbH Leipzig for the analysis. Furthermore, the authors would like to thank the company ABB for the provision of comparative data.; 21st International Symposium on High Voltage Engineering, ISH 2019 ; Conference date: 26-08-2019 Through 30-08-2019",
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AU - Suwarno,

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N1 - Funding information: Acknowledgments. The authors would like to express their graduate to GRIDINSPECT GmbH and AiF/ZiM for the financial support as well as Weidmann Electrical Technology AG for the support with insulation materials and Analysen Service GmbH Leipzig for the analysis. Furthermore, the authors would like to thank the company ABB for the provision of comparative data. The authors would like to express their graduate to GRIDINSPECT GmbH and AiF/ZiM for the financial support as well as Weidmann Electrical Technology AG for the support with insulation materials and Analysen Service GmbH Leipzig for the analysis. Furthermore, the authors would like to thank the company ABB for the provision of comparative data.

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