Advancing Transformer Asset Management with Geographic Information Systems

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Sinung Suakanto, Chandra Wiharya, Hilda Nuraliza, Mifta Ardianti, Riska Yanu Farifah, Taufik Nur Adi

2024 2024 International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2024 Conference paper Cited by 0 Quartile

Abstract

The increasing demand for electricity supply due to population growth necessitates not only an optimal quantity but also high-quality electrical distribution. The vulnerability of electrical distribution systems to disturbances underscores the critical need for effective monitoring and maintenance of transformers to prevent failures and premature performance degradation. This research aims to develop a comprehensive Geographic Information System (GIS) for monitoring electrical transformer assets using the Design Science Research Methodology (DSRM). The proposed system involves equipping transformers with advanced IoT devices that continuously transmit data to a centralized server, enabling real-time monitoring of transformer location, condition, and health. This data is then presented interactively on a digital map, providing comprehensive visual insights for maintenance and operational decision-making. The GIS integrates both spatial and non-spatial data, allowing for a detailed analysis of transformer performance across large geographical areas. The implementation of this GIS-based system is expected to significantly enhance operational efficiency, enabling proactive and preventive maintenance strategies, and reducing the risk of sudden failures within the electrical distribution network. By facilitating timely detection and resolution of potential issues, this system aims to ensure the reliability and stability of the electricity supply, ultimately contributing to improved service quality, reduced maintenance costs, and extended transformer lifespan. Furthermore, the system supports data-driven planning for future network expansions and upgrades, promoting a more resilient and robust power distribution infrastructure. © 2024 IEEE.

Affiliations

Telkom University, Department of Information System, Bandung, Indonesia; Politeknik Negeri Malang, Department of Electrical Engineering, Bandung, Indonesia