Optimizing Preventive Maintenance for DC Battery Back-Up Systems in Gas Turbine Compressors
DOI:
https://doi.org/10.70550/joseb.v3i1.347Keywords:
DC Battery Back-Up, Gas Turbine Compressor, Battery Capacity Degradation, Preventive Maintenance, Reliability AnalysisAbstract
Objectives: In general, the objective of this Capstone Project is to formulate an optimal preventive maintenance strategy for the DC Battery Backup Control System to support the operational sustainability of Gas Turbine Compressors in the oil and gas sector.
Findings: Unit shutdown on July 21, 2024, triggered by a main power supply failure (220 VAC). The battery VRLA (Valve Regulated Lead Acid) type, with a constant load of 10A, the battery should be able to support the load without a 220 Vac power supply for 8 to 10 hours. However, in practice, it can only sustain the load for less than 5 minutes.
Methodology: This study employs a mixed-methods approach, integrating both qualitative and quantitative data. Qualitative data were collected through interviews involving managers, supervisors, and technicians, as well as direct field observations. Quantitative data were obtained from daily operational reports and historical analyzer records. The problem analysis strategy was conducted using a Fishbone Diagram and the 5-Why analysis tool to systematically identify root causes.
Conclusion: Based on field observations and technical analysis, battery capacity degradation from its original specification was identified, resulting in the failure of the DC backup battery to sustain the load during the loss of the 220 VAC main power supply. The Fishbone Analysis and 5-Why approach further revealed that human factors played a significant role in contributing to the failure. Based on these findings, corrective actions were implemented, including battery replacement and improvement of the maintenance strategy. Final testing demonstrated a significant improvement in system reliability, with the batteries capable of supporting the control load stably in accordance with operational requirements.
Downloads
References
Hardiansyah, H., Franciscus, F., & Yuniarti, E. (2024). Analisis Keandalan Main Battery Peshawar CRJ-1000 Di Maskapai Garuda Indonesia. Jurnal Teknologi Kedirgantaraan, 9(1), 59–68. https://doi.org/10.35894/jtk.v9i1.106
Humainah, R. F., Suhendar, & Rizky, Y. (2023). Analisis Penyebab Terjadi Eror Dalam Tegangan Baterai 110 V Pada Gardu Induk Sepatan. Teknika, 8(2), 66–73. https://doi.org/10.52561/teknika.v8i2.290
IEEE. (2006). IEEE Recommended Practice for Maintenance, Testing, and Replacement of Valve‐Regulated Lead‐Acid (VRLA) Batteries for Stationary Applications. IEEE Std 1188-2005 (Revision of IEEE Std 1188-1996), 1–44.
Ihsan, A. N., Joko, Suprianto, B., & Wrahatnolo, T. (2022). Analisis dan Efisiensi Kebutuhan Kapasitas Baterai 110 Volt DC Gas Insulated Switchgear (GIS) 150 KV Wonokromo Surabaya. Jurnal Teknik Elektro, 11(3).
Iskandar, H. R., Elysees, C. B., Ridwanulloh, R., Charisma, A., & Yuliana, H. (2021). Analisis Performa Baterai Jenis Valve Regulated Lead Acid pada PLTS Off-grid 1 KWP. Jurnal Teknologi Universitas Muhammadiyah Jakarta, 13(2), 129–140.
Kostenko, G. (2025). Cluster Based Deployment of Second Life Batteries for Reliable and Sustainable Backup Power Solution in Power System. System Research in Energy, 2025(1), 40–60. https://doi.org/10.15407/srenergy2025.01.040
Li, X., Yang, W., Pang, A., Jiang, C., Zhao, Q., & Haider, S. N. (2022). A Fault Diagnosis Method for VRLA Battery in Data Center. Energy Reports, 8, 14220–14235. https://doi.org/10.1016/j.egyr.2022.10.380
Nugroho, R. E., & Khoirudin, S. (2020). Overall Equipment Effectiveness Improvement on Cutting Machine by Minimizing Six Big Losses. Saudi Journal of Business and Management Studies, 5(1), 84–88.
Samuelle, M. (2024). Solving Cell Voltage Unbalance: Strategy for Quality Improvement in Lithium-Ion Battery Production at FPT Industrial. Doctoral Dissertation, Politecnico di Torino.
Ulansky, V., & Raza, A. (2024). A Historical Survey of Corrective and Preventive Maintenance Models with Imperfect Inspections: Cases of Constant and Non-Constant Probabilities of Decision Making. Aerospace, 11(1), 92.
Vaghela, R., Ramani, P., Sarda, J., Hui, K. L., & Sain, M. (2024). Analysis of State‐of‐Health Estimation Approaches and Constraints for Lithium‐Ion Batteries in Electric Vehicles. International Journal of Energy Research, 2024(1). https://doi.org/10.1155/2024/6488186
Yu, R., Liu, G., Xu, L., Ma, Y., Wang, H., & Hu, C. (2023). Review of Degradation Mechanism and Health Estimation Method of VRLA Battery Used for Standby Power Supply in Power System. Coatings, 13(3), 485. https://doi.org/10.3390/coatings13030485
Zahra, M. M. A., Sharif, H., Mohammed, N. Q., Ali, A. A., Tariq, H. T., & Mohammed, M. Q. M. (2023). Battery Charging Monitoring System Using PZEM 004t Sensor and DC Voltage Sensor. International Journal of Renewable Energy Research, 13(2), 666–672.
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Journal of Sustainable Economic and Business
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
