Prediction of Age Loss on 160 KVA Transformer PT. PLN ULP Kenjeran Surabaya using The Linear Regression Method

Reza Sarwo Widagdo; Aris Heri Andriawan

doi:10.30595/jrre.v5i2.18140

Authors

Reza Sarwo Widagdo Department of Electrical Engineering, Universitas 17 Agustus 1945 Surabaya
Aris Heri Andriawan Department of Electrical Engineering, Universitas 17 Agustus 1945 Surabaya

DOI:

https://doi.org/10.30595/jrre.v5i2.18140

Abstract

Distribution transformer is one of the important equipment in the distribution of electricity to consumers. The electricity demand increases every year, so that the transformer works optimally, it must also be considered regarding the loading. According to IEC 354 if the transformer is loaded stable 80% with conditions around 20â„ƒ and the winding temperature is 98â„ƒ, but if the ambient temperature is more than 20â„ƒ then the age of the transformer will decrease. With an average loading of 71.75%, based on the calculation that the predicted useful age of the 160 KVA distribution transformer in 2027 will have an age loss index of 1.1 p.u, so it is estimated that the remaining age of the distribution transformer is 12 years and 7 months. Analysis using a statistical approach assisted by SPSS software was also carried out to see how much influence the loading has on the age loss of the transformer.

Author Biographies

Reza Sarwo Widagdo, Department of Electrical Engineering, Universitas 17 Agustus 1945 Surabaya

Department of Electrical Engineering, Universitas 17 Agustus 1945 Surabaya

Aris Heri Andriawan, Department of Electrical Engineering, Universitas 17 Agustus 1945 Surabaya

Department of Electrical Engineering, Universitas 17 Agustus 1945 Surabaya

References

[1] Delboni, L. F., Marujo, D., Balestrassi, P. P., & Oliveira, D. Q. (2019). Electrical power systems: Evolution from traditional configuration to distributed generation and microgrids. Microgrids design and implementation, 1-25.

[2] Tenbohlen, S., Coenen, S., Djamali, M., Müller, A., Samimi, M. H., & Siegel, M. (2016). Diagnostic measurements for power transformers. Energies, 9(5), 347.

[3] Sun, C. C., Xiao, C., Hou, J., Kong, L., Ye, J., & Yu, W. J. (2020, October). Analysis of Factors Affecting Temperature Rise of Oil-immersed Power Transformer. In Journal of Physics: Conference Series (Vol. 1639, No. 1, p. 012087). IOP Publishing.

[4] Stanelyte, D., & Radziukynas, V. (2019). Review of voltage and reactive power control algorithms in electrical distribution networks. Energies, 13(1), 58.

[5] Usman, M., Bignucolo, F., Turri, R., & Cerretti, A. (2017, August). Power losses management in low voltage active distribution networks. In 2017 52nd International Universities Power Engineering Conference (UPEC) (pp. 1-6). IEEE.

[6] Pan, Y., Han, S., Feng, J., & Hu, X. (2020). An analytical electromagnetic model of “Sen” transformer with multi-winding coupling. International Journal of Electrical Power & Energy Systems, 120, 106033.

[7] Bina, M. T., & Kashefi, A. (2011). Three-phase unbalance of distribution systems: Complementary analysis and experimental case study. International Journal of Electrical Power & Energy Systems, 33(4), 817-826.

[8] Bunn, M., Das, B. P., Seet, B. C., & Baguley, C. (2019). Empirical design method for distribution transformer utilization optimization. IEEE Transactions on Power Delivery, 34(4), 1803-1813.

[9] Sodilesmana, A. E., Nasrulloh, N., & Prasetyono, R. N. (2021). The Effect of Loading and Unbalanced Load on Determination of Life Loss of Distribution Transformers. Journal of Electronic and Electrical Power Applications, 1(2), 1-7.

[10] Dao, T., & Phung, B. T. (2018). Effects of voltage harmonic on losses and temperature rise in distribution transformers. IET Generation, Transmission & Distribution, 12(2), 347-354.

[11] Murugan, R., & Ramasamy, R. (2019). Understanding the power transformer component failures for health index-based maintenance planning in electric utilities. Engineering Failure Analysis, 96, 274-288.

[12] Oliveira, M. M., Bender, V., Marchesan, T. B., Kaminski, A. M., Medeiros, L. H., Wilhelm, H. M., & Neto, J. B. F. (2020, September). Power transformers assessment applying health index and apparent age methods. In 2020 IEEE PES Transmission & Distribution Conference and Exhibition-Latin America (T&D LA) (pp. 1-6). IEEE.

[13] Susa, D., & Nordman, H. (2013). IEC 60076–7 Loading Guide Thermal Model Constants Estimation. International transactions on electrical energy systems, 23(7), 946-960.

[14] Vasquez, W. A., & Jayaweera, D. (2020). Risk‐based approach for power transformer replacement considering temperature, apparent age, and expected capacity. IET Generation, Transmission & Distribution, 14(21), 4898-4907.

[15] Sah, R. M., & Srivastava, J. (2013). Modelling And Simulation of Distribution Transformer for Analysing the Transformer Losses Using Analytical and Simulation Method. International Journal of Engineering Research and Applications (IJERA) ISSN, 2248-9622.

[16] Sim, H. J., & Digby, S. H. (2017). Power transformers. In Electric power transformer engineering (pp. 2-1). CRC Press.

[17] Diantari, R. A., & Fitri, V. A. (2022, November). Analysis of the Effect of Loading on Age Loss and Efficiency on Dry Type Transformer at PT MRT Jakarta. In 2022 5th International Conference on Power Engineering and Renewable Energy (ICPERE) (Vol. 1, pp. 1-6). IEEE.

[18] Kim, Y., Son, H. G., & Kim, S. (2019). Short term electricity load forecasting for institutional buildings. Energy Reports, 5, 1270-1280.

[19] , C. C., Xiao, C., Hou, J., Kong, L., Ye, J., & Yu, W. J. (2020, October). Analysis of Factors Affecting Temperature Rise of Oil-immersed Power Transformer. In Journal of Physics: Conference Series (Vol. 1639, No. 1, p. 012087). IOP Publishing.

[20] Velásquez, R. M. A., Lara, J. V. M., & Melgar, A. (2019). Converting data into knowledge for preventing failures in power transformers. Engineering Failure Analysis, 101, 215-229.