Main Article Content
Abstract
The continuous increase in electrical energy demand, particularly in semi-urban areas, has created significant challenges for the reliability and operational performance of power distribution systems. One critical problem is the occurrence of overload conditions on distribution transformers, which may accelerate insulation degradation, increase thermal stress, and reduce equipment lifespan. This study aims to evaluate the effectiveness of installing an inserted transformer as a technical solution to mitigate overload in the medium-voltage distribution network of PT PLN (Persero) ULP Abepura, Koya Barat. A descriptive quantitative case study approach was employed using field measurement data from the ABE-262 distribution transformer before and after the installation of a 160 kVA inserted transformer. The measured parameters included phase current, voltage profile, transformer loading percentage, phase imbalance, and neutral current during peak load time (WBP) and off-peak load time (LWBP). The results show that the loading of the main transformer decreased from 92.40% to 63.12% during WBP and from 78.94% to 26.56% during LWBP. Meanwhile, the inserted transformer absorbed only 13.32% of the total load during WBP and 9.47% during LWBP, indicating the availability of reserve capacity for future demand growth. The installation also improved phase balance, as shown by the reduction in phase imbalance from 12.4% to 5.6%, and reduced neutral current from 69.7 A to 49.3 A during LWBP. These findings confirm that the inserted transformer is an effective, economical, and practical solution for reducing transformer overload, improving load distribution, and enhancing distribution system reliability. In addition, this strategy provides operational redundancy and reserve capacity, thereby supporting the long-term resilience of distribution networks in areas with limited infrastructure.
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References
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References
Addae, R. K., & Brown, C. (2025). The role of artificial intelligence in enhancing human longevity: Mitigating cognitive overload for extended lifespan among master’s students in mathematics at the Catholic University of Ghana. Golden Ratio of Social Science and Education, 5(2), 302–318. https://doi.org/10.52970/grsse.v5i2.1275
Anjas, W. S., & Ilham, M. (2022). Analysis of transformer loading before the addition of an inserted substation to improve distribution transformer capacity. Vertex Elektro, 14(2), 90–101. https://doi.org/10.26618/jte.v14i2.10277
Azeem, F., Khan, M. A., Ali, M., & Rehman, S. U. (2026). Performance assessment of distribution transformers under emerging residential load conditions. Energy Conversion and Management, 310, 117112. https://doi.org/10.1016/j.enconman.2025.117112
Billinton, R., & Allan, R. N. (2022). Reliability evaluation of power systems (2nd ed.). Springer.
Brown, R. E. (2022). Electric power distribution reliability (2nd ed.). CRC Press.
Diahovchenko, I., et al. (2022). Mitigation of transformers’ loss of life in power distribution networks with high penetration of electric vehicles. Results in Engineering, 15. https://doi.org/10.1016/j.rineng.2022.100592
Elpisah, E., Suarlin, S., & Yahya, M. (2021). Klassen typology and Williamson index to measure macroeconomics in South Sulawesi Province. Golden Ratio of Social Science and Education, 1(1), 37–49. https://doi.org/10.52970/grsse.v1i1.109
Gönen, T. (2023). Electric power distribution engineering (4th ed.). CRC Press.
Hussain, A., Bui, V. H., & Kim, H. M. (2023). A decentralized dynamic pricing model for demand management of electric vehicles. IEEE Access, 11, 13191–13201. https://doi.org/10.1109/ACCESS.2023.3242599
IEEE. (2011). IEEE guide for loading mineral-oil-immersed transformers and step-voltage regulators. IEEE. https://doi.org/10.1109/IEEESTD.2012.6166928
Jain, A., & Karimi-Ghartemani, M. (2022). Mitigating adverse impacts of increased electric vehicle charging on distribution transformers. Energies, 15(23). https://doi.org/10.3390/en15239023
Krstivojević, J., Popović, D., Stojanović, Z., & Mitrović, N. (2025). Enhancing reliability performance in distribution networks through optimal investment strategies under financial constraints. Applied Sciences, 15(8), 4209. https://doi.org/10.3390/app15084209
Kumar, P., Singh, R. K., & Sharma, N. (2024). Impact of load imbalance on distribution transformer efficiency and mitigation techniques. IEEE Access, 12, 45678–45690. https://doi.org/10.1109/ACCESS.2024.3356789
Mehmood, K. T., & Hussain, M. M. (2025). Dynamic load management in modern grid systems using an intelligent SDN-based framework. Energies, 18(12). https://doi.org/10.3390/en18123001
Min, Q., et al. (2025). A dissolved gas prediction method for transformer on-load tap changer oil integrating anomaly detection and deep temporal modeling. Energies, 18(19), 5079. https://doi.org/10.3390/en18195079
Muhammad, M., Meliala, S., & Damayanti, D. (2022). Overcoming overload in distribution transformers using inserted transformers at PT PLN (Persero) ULP Langsa Kota. Jurnal Energi Elektrik, 11(1), 29. https://doi.org/10.29103/jee.v11i1.7735
Nurhidayah, S., Callo, H., & Halim, A. (2024). The influence of Cooperative Lending Sejahtera Bahari to small and medium enterprise development in Mamuju District, Indonesia. Golden Ratio of Social Science and Education, 4(2), 263–271. https://doi.org/10.52970/grsse.v4i2.1054
Odongo, G. Y., Musabe, R., Hanyurwimfura, D., & Bakari, A. D. (2022). An efficient LoRa-enabled smart fault detection and monitoring platform for the power distribution system using self-powered IoT devices. IEEE Access, 10, 73403–73420. https://doi.org/10.1109/ACCESS.2022.3189002
Rahmawati, Y., et al. (2024). Load forecasting analysis for estimating transformer capacity of Karangkates substations using Holt-Winters method in Python. International Journal of Power Electronics and Drive Systems (IJPEDS), 15(4), 2222–2233. https://doi.org/10.11591/ijpeds.v15.i4.pp2222-2233
Razzaghi, A., Hosseini, S. M., & Parvania, M. (2026). Reliability-, security-, and flexibility-oriented distribution network expansion planning in modern power systems. Energy Reports, 12, 1001–1015. https://doi.org/10.1016/j.egyr.2026.01.015
Rizal, M., Azis, A., Perawati, & Irwansi, Y. (2025). Analysis of the impact of load imbalance on neutral current and power losses in power transformers. International Journal of Electrical Engineering, Mechatronics and Computer Science, 3(1), 12–20.
Rouholamini, M., Shahidehpour, M., & Khodaei, A. (2025). Resiliency of electric power distribution systems: Concepts, metrics, and improvement strategies. Energy Informatics, 8(1), 45. https://doi.org/10.1186/s43065-025-00154-y
Roy, P., et al. (2023). Impact of electric vehicle charging on power distribution systems: A case study of the grid in Western Kentucky. IEEE Access, 11, 49002–49023. https://doi.org/10.1109/ACCESS.2023.3276928
Short, T. A. (2023). Electric power distribution handbook (3rd ed.). CRC Press.
Sinurat, A. F. (2026). Optimization of three-phase load balancing to improve transformer efficiency and reduce neutral current. Journal of Electrical Engineering and Computer Science, 14(2), 89–98.
Staszewski, L., Kaczmarek, M., & Ziółkowski, P. (2025). A parametric comparison of IEC 60076-7 and IEEE C57.91 transformer thermal-aging models. Energies, 18(24), 6469. https://doi.org/10.3390/en18246469
Willis, H. L., & Scott, W. G. (2021). Distributed power generation: Planning and evaluation. CRC Press.
Zhang, H., Sinha, R., Golmohamadi, H., Chaudhary, S. K., & Bak-Jensen, B. (2025). Autonomous control of electric vehicles using voltage droop. Energies, 18(11). https://doi.org/10.3390/en18112824
Zhang, W., Liu, S., Li, M., Bao, H., Yuan, S., & Cheng, X. (2025). A method for load forecasting of distribution transformers based on parameter-efficient fine-tuning of large language models in power system. Processes, 13(9). https://doi.org/10.3390/pr13092986