Analisis Health Index Transformator Distribusi Inti Amorphous Untuk Penentuan Skala Prioritas Pemeliharaan Menggunakan Metode AHP-TOPSIS

Tedy Heryadi

doi:10.36418/syntax-literate.v10i12.62830

Tedy Heryadi Institut Teknologi PLN, Indonesia

DOI: https://doi.org/10.36418/syntax-literate.v10i12.62830

Keywords: Health Index, AHP, TOPSIS, amorphous core distribution transformer, maintenance prioritization

Abstract

Amorphous core distribution transformers are increasingly adopted in PLN due to their superior magnetic efficiency and lower core losses. However, these transformers also have the risk of damage that can reduce the reliability of electricity distribution. This study aims to determine the parameter weightings for the Health Index (HI), develop an HI model based on the integrated Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and generate a prioritized maintenance ranking for amorphous transformers. The AHP method was employed to calculate the weights of seven key diagnostic parameters, resulting in weights of physical condition (0.040), oil leakage (0.163), temperature (0.145), grounding (0.159), load imbalance (0.189), load profile (0.140), and noise level (0.164). Subsequently, TOPSIS was applied to rank 22 transformer units, showing that transformer BTDA110 achieved the highest maintenance priority (ranked 22 based on the lowest health index value), followed by GYPA110 and LITA110, whereas PTP110 held the lowest priority (ranked 1). These findings demonstrate that the combined AHP-TOPSIS approach effectively integrates real condition monitoring data into a quantitative decision-making framework, supporting strategic asset management. The practical implication of this study is the development of an adaptive maintenance prioritization scale, which is expected to enhance power delivery reliability, reduce the risk of transformer failure, and optimize operational expenditure for electric utilities.

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References

[1] A. Abu-Siada, S. Hmood, and S. Islam, A New Fuzzy Logic Approach for Consistent Interpretation of Dissolved Gas Analysis, IEEE Trans. Dielectr. Electr. Insul., vol. 20, no. 6, pp. 2343-2349, 2013.
[2] S. D. J. McArthur et al., Multi-Agent Systems for Power Engineering Applications Part I: Concepts, Approaches, and Technical Challenges, IEEE Trans. Power Syst., vol. 22, no. 4, pp. 1743-1752, 2007.
[3] M. Arshad and S. M. Islam, Significance of cellulose power transformer condition assessment, IEEE Trans. Dielectr. Electr. Insul., vol. 18, no. 5, pp. 1591-1598, 2011.
[4] IEEE Std C57.12.00, IEEE Standard for General Requirements for Liquid-Immersed Distribution, Power, and Regulating Transformers, 2015.
[5] PT PLN, Edaran Direksi No.17 tahun 2014 tentang Metode Pemeliharaan Trafo Distribusi Berbasis Kaidah Manajemen Aset, 2014.
[6] R. Giglioli, G. Lutzemberger, and L. Sani, Use of AMT Transformers and Distributed Storage Systems to Enhance Electrical Feeding Systems for Tramways, Energies, vol. 13, no. 18, p. 4725, 2020.
[7] A. Azmi, J. Jasni, N. Azis, and M. Z. A. A. Kadir, Evolution of transformer health index in the form of mathematical equation, Renew. Sustain. Energy Rev., vol. 76, pp. 687-700, 2017.
[8] T. L. Saaty, How to make a decision: The analytic hierarchy process, Eur. J. Oper. Res., vol. 48, no. 1, pp. 9-26, 1990.
[9] C. L. Hwang and K. Yoon, Multiple Attribute Decision Making: Methods and Applications, Springer-Verlag, New York, 1981.
[10] W. H. Bartley, Analysis of Transformer Failures, International Association of Engineering Insurers, 36th Annual Conference, Stockholm, 2003.
[11] G. C. Jaiswal, M. S. Ballal, P. A. Venikar, D. R. Tutakne, and H. M. Suryawanshi, Genetic algorithm-based health index determination of distribution transformer, Int. Trans. Electr. Energy Syst., vol. 28, no. 5, pp. 1-12, 2018.
[12] R. Suharly, Suwarno, and M. S. Hadi, Condition Monitoring and Health Index Determination of Operating 20kV Distribution Transformers using Analytical Hierarchy Process Method, 6th Int. Conf. Power Eng. Renew. Energy, ICPERE 2024.
[13] J. Wen, S. Lin, X. Qu, and Q. Xiao, A TOPSIS-Based Vulnerability Assessment Method of Distribution Network Considering Network Topology and Operation Status, IEEE Access, vol. 11, pp. 94358-94370, 2023.
[14] Y. Huang, Y. Jiang, and J. Wang, Adaptability Evaluation of Distributed Power Sources Connected to Distribution Network, IEEE Access, vol. 9, pp. 42409-42423, 2021.
[15] M. Bartlomiejczyk, M. Gutten, and S. Hamacek, Analysis of transformer state by fuzzy TOPSIS and AHP method, Proc. 2014 15th Int. Sci. Conf. Electr. Power Eng. EPE 2014, pp. 451-456, 2014.