Abstract
The results of analysis of transformer oils ageing under long-term operation conditions for 231 transformers of 110 kV voltage are presented. The procedure of statistical processing of transformer oil in-service test results is proposed. Significant influence of transformers operating conditions on oil ageing intensity is shown. The analysis of dependences of 7 oil indicators on operating time on a deviation from linearity has been carried out. It is established that under long-term operation the values of indicators do not change linearly. The characteristic sections of the indicators dependences are distinguished, and the physical interpretation of the obtained results is given. Correlation dependences between oil indicators have been analysed.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abdi S, Harid N, Safiddine L, Boubakeur A, Haddad A (2021) The correlation of transformer oil electrical properties with water content using a regression approach. Energies 14:2089. https://doi.org/10.3390/en14082089
Bhatia N, El-Hag A, Shaban K (2020) Machine learning-based regression and classification models for oil assessment of power transformers. 2020 IEEE international conference on informatics, IoT, and enabling technologies (ICIoT) 400–403. doi: https://doi.org/10.1109/iciot48696.2020.9089647
Bondarenko VO, Shutenko OV (2009) Improving decision-making procedures in assessing the degree of aging of transformer oils. ELECTRO Electr Eng, Electr Power Indus, Electr Indus 1:17–21 ((in Russian))
Diwyacitta K, Prasojo R (2017a) Study on correlation among oil dielectric characteristics, dissolved gases, and operating life of 150 kV power transformer. Int J Electr Eng Informatics 9:585–602. https://doi.org/10.15676/ijeei.2017.9.3.12
Diwyacitta K, Prasojo R, Suwarno, Gumilang H (2017b) Effects of loading factor in operating time on dielectric characteristics of transformer oil. 2017b international conference on high voltage engineering and power systems (ICHVEPS). doi: https://doi.org/10.1109/ichveps.2017.8225968
Forouhari S, Abu-Siada A (2018) Application of adaptive neuro fuzzy inference system to support power transformer life estimation and asset management decision. IEEE Trans Dielectr Electr Insul 25:845–852. https://doi.org/10.1109/tdei.2018.006392
Gautam L, Kumar R, Sood Y (2020) Identifying transformer oil criticality using fuzzy logic approach. IEEE Students Conf Eng Syst (SCES) 2020:1–6. https://doi.org/10.1109/sces50439.2020.9236724
Gmurman VE (1977) Probability theory and mathematical statistics. High.school, Moscow (in Russian)
Gouda O, El Dein A (2019) Prediction of aged transformer oil and paper insulation. Electr Power Components Syst 47(4–5):406–419. https://doi.org/10.1080/15325008.2019.1604848
IEC 60422 (2012) Mineral insulating oils in electrical equipment - Supervision and maintenance guidance.
Ivanov KI, Zhahovskaya VP (1962) About the nature of water-soluble acids formed in the initial stage of aging of energy oils. Chem Technol Fuels Oils 7:58–63 ((in Russian))
Johnson NL, Leone FC (1977) Statistics and experimental design in engineering and the physical sciences: v 1 (probability & mathematical statistics s.). Wiley
Kaliappan G, Rengaraj M (2021) Aging assessment of transformer solid insulation: a review. Mater Today: Proc 47:272–277. https://doi.org/10.1016/j.matpr.2021.04.301
Kozlov V, Valiullina D, Kurakina O (2021) Visual determination of transformer oil quality parameters. Problemele Energeticii Regionale 2(50):25–34. https://doi.org/10.52254/1857-0070.2021.2-50.03(inRussian)
Lipstein RA, Shakhnovich MI (1983) Transformer oil. Energoatomizdat, Moscow
Liu J, Fan X, Zheng H, Zhang Y, Zhang C, Lai B, Wang J, Ren G, Zhang E (2019) Aging condition assessment of transformer oil-immersed cellulosic insulation based upon the average activation energy method. Cellulose 26:3891–3908. https://doi.org/10.1007/s10570-019-02331-1
Liu J, Zhang H, Geng C, Fan X, Zhang Y (2021) Aging assessment model of transformer insulation based on furfural indicator under different oil/pressboard ratios and oil change. IEEE Trans Dielectr Electr Insul 28:1061–1069. https://doi.org/10.1109/tdei.2021.009530
Mahanta D, Andrew O (2020) Transformer dielectric liquid: a review. IEEE PES/IAS PowerAfrica 2020:1–5. https://doi.org/10.1109/powerafrica49420.2020.9219867
Matharage S, Liu S, Liu Q, Wang Z (2019) Investigation on the acid removal performance of oil regeneration sorbent materials. Lect Notes Elect Eng. https://doi.org/10.1007/978-3-030-31676-1_81
Mehmood M, Li J, Wang F, Huang Z, Ahmad J, Bhutta M (2018) Analyzing the health condition and chemical degradation in field aged transformer insulation oil using spectroscopic techniques. Int Conf Diagnost Electr Eng (diagnostika) 2018:1–4. https://doi.org/10.1109/diagnostika.2018.8526138
Meshkatoddini MR (2008) Aging study and lifetime estimation of transformer mineral oil. Am J Eng Appl Sci 1(4):384–388. https://doi.org/10.3844/ajeassp.2008.384.388
Nurcahyanto H, Nainggolan J, Ardita I, Hudaya C (2019) Analysis of power transformer’s lifetime using health index transformer method based on artificial neural network modeling. Int Conf Electr Eng Informatics (ICEEI) 2019:574–579. https://doi.org/10.1109/iceei47359.2019.8988870
Ojha SK, Purkait P, Chakravorti S (2017) Evaluating the effects of lower molecular weight acids in oil-paper insulated transformer. 2017 3rd International Conference on Condition Assessment Techniques in Electrical Systems (CATCON) 138–143. doi: https://doi.org/10.1109/catcon.2017.8280200
Senoussaoui MEA, Brahami M, Fofana I (2021) Transformer oil quality assessment using random forest with feature engineering. Energies 14:1809. https://doi.org/10.3390/en14071809
Shteger G (1961) Insulating material. Gosenergoizdat
Shutenko O, Ponomarenko S (2020a) Analysis of the impact of power transformer loading on the transformer oil aging intensity. IEEE KhPI Week Adv Technol (KhPIWeek) 2020:76–81. https://doi.org/10.1109/khpiweek51551.2020.9250159
Shutenko O, Ponomarenko S (2020b) Diagnostics of transformer oils using the multiple linear regression model. 2020b IEEE Problems of automated electrodrive theory and practice (PAEP). doi: https://doi.org/10.1109/paep49887.2020.9240875
Shutenko O, Ponomarenko S (2020c) Reliability assessment of the results of periodic monitoring of the transformer oils condition. 2020c IEEE 4th international conference on intelligent energy and power systems (IEPS). doi: https://doi.org/10.1109/ieps51250.2020.9263141
Shutenko OV (2008) Complex correlation analysis of quality parameters in the transformer oil. Bulletin of NTU "KPI" Series "problems of electrical machines and apparatus perfection. the theory and practice" 45:161–172 (in Russian)
Shutenko OV, Baklaj DN (2013) Planning of experimental studies in the power sector. The methods of experimental data processing. NTU" KHPI", Kharkov (in Russian)
Shutenko OV, Zagaynova AA, Serdyukova GN (2019) Analysis of operating conditions and modes influence on technical state of main insulation of high-voltage bushings of different design. Electr Eng Electromech 1:57–66. https://doi.org/10.20998/2074-272x.2019.1.10
Singh H, Singh J (2020) Enhanced optimal trained hybrid classifiers for aging assessment of power transformer insulation oil. World J Eng 17:407–426. https://doi.org/10.1108/wje-11-2019-0339
Smurov AA, Kurlin MV (1935) Aging oils and dielectric losses. Electricity 9:9–11 ((in Russian))
SOU-N EE 43–101:2009 (2018) Receiving, use and exploitation of transformer oils. Quality assessment standards. Kyiv (in Ukrainian)
Srividhya V, Babu J, Sujatha K, Veerendrakumar J, Aruna M, Shafiya S, SaiKrishna AM (2021) Determination of breakdown voltage for transformer oil testing using ANN. Adv Intell Syst Comput. https://doi.org/10.1007/978-981-33-6981-8_35
Uzair MAH, Banakara B (2016) Failure analysis of power transformers by DGA, oil tests and markov approach. Int J Eng Appl Sci Technol (IJEAST) 1:250–255
Wahab MAA, Hamada MM, El-Tallawy AAA, Ismail G (2008) A new non-linear model for transformer oil residual operating time. 2008 12th international middle-east power system conference 66–70. doi: https://doi.org/10.1109/mepcon.2008.4562315
Wu-liang D (2019) Analysis of life cycle characteristics of power transformer based on linear regression. IOP Conf Ser: Earth Environ Sci 223:012029. https://doi.org/10.1088/1755-1315/223/1/012029
Funding
Not applicable.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Rights and permissions
About this article
Cite this article
Shutenko, O., Ponomarenko, S. Analysis of Ageing Characteristics of Transformer Oils under Long-Term Operation Conditions. Iran J Sci Technol Trans Electr Eng 46, 481–501 (2022). https://doi.org/10.1007/s40998-022-00492-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40998-022-00492-7