Smart Management of Power Transformers: A GIS and IoT Approach for Improved Efficiency

The integration of Geographic Information Systems (GIS) and the Internet of Things (IoT) is explored for smart management of power transformers, essential for maintaining efficient and stable electricity distribution. As the demand for reliable energy grows, advanced technologies are increasingly applied to enhance transformer monitoring and reduce operational downtime. IoT-based sensors enable the system to collect real-time data on transformer conditions, while GIS mapping allows for the visualization of asset locations and performance. This approach supports continuous monitoring, early detection of potential issues, and timely maintenance interventions. By optimizing maintenance scheduling and resource allocation, the system reduces the risk of transformer failures, improves service reliability, and generates significant cost savings. Case studies and simulations demonstrate the effectiveness of this integrated method, highlighting its scalability and potential for widespread implementation in modern power grids. The combination of GIS and IoT offers a data-driven solution to power transformer management, fostering smarter and more resilient electrical infrastructure. Lastly, key findings indicate the system's ability to reduce transformer downtime by up to 30<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>, improve maintenance efficiency by 25<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>, and achieve cost savings of approximately 20% compared to conventional methods, showcasing its transformative potential for modern energy management.

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Publication Details

Published
2024-12-11
DOI
https://doi.org/10.1109/icaaeei63658.2024.10899155
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
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article

Smart Management of Power Transformers: A GIS and IoT Approach for Improved Efficiency

Ahmad Hermawan, Ferdian Ronilaya, Mohammad Noor Hidayat, Satria Luthfi Hermawan et al.
Power Transformer Diagnostics and Insulation
article

Smart Management of Power Transformers: A GIS and IoT Approach for Improved Efficiency

Ahmad Hermawan, Ferdian Ronilaya, Mohammad Noor Hidayat, Satria Luthfi Hermawan, Chandra Wiharya, Hilman Rangga Nugraha Hermawan
article en

Abstract

The integration of Geographic Information Systems (GIS) and the Internet of Things (IoT) is explored for smart management of power transformers, essential for maintaining efficient and stable electricity distribution. As the demand for reliable energy grows, advanced technologies are increasingly applied to enhance transformer monitoring and reduce operational downtime. IoT-based sensors enable the system to collect real-time data on transformer conditions, while GIS mapping allows for the visualization of asset locations and performance. This approach supports continuous monitoring, early detection of potential issues, and timely maintenance interventions. By optimizing maintenance scheduling and resource allocation, the system reduces the risk of transformer failures, improves service reliability, and generates significant cost savings. Case studies and simulations demonstrate the effectiveness of this integrated method, highlighting its scalability and potential for widespread implementation in modern power grids. The combination of GIS and IoT offers a data-driven solution to power transformer management, fostering smarter and more resilient electrical infrastructure. Lastly, key findings indicate the system's ability to reduce transformer downtime by up to 30<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>, improve maintenance efficiency by 25<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup>, and achieve cost savings of approximately 20% compared to conventional methods, showcasing its transformative potential for modern energy management.

State University of Malang (ID)
Affordable and clean energy
Openalex Percentile: Top 74%
Power Transformer Diagnostics and Insulation
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