Design of an Intelligent PLC-Based Protection for Power Transformers with Auto-Re-Closer
This paper presents a design of a protection system used for a Power transformer using PLC. Transformers are critical components in power systems, and their protection is paramount due to their variable load conditions, which lead to fluctuating currents and potential faults. Traditional manual monitoring or microcontroller-based systems are often used, which are found to be less accurate and more labour-intensive. The system’s implementation underscores its effectiveness in ensuring the safe and efficient operation of transformers in industrial settings. By integrating advanced fault detection, automatic trip mechanisms, and adaptive control functionalities, the system enhances operational reliability while safeguarding equipment against potential damage or operational disruptions. The proposed system leverages PLCs for their superior speed, performance, and reliability, integrating relays and sensors to detect faults such as overloading, overvoltage, under-voltage, phase-to-phase faults, and overheating. This PLC-based approach ensures continuous, efficient, and precise monitoring. Major Findings: It enhances operational efficiency, reliability, and safety while reducing maintenance time and human error. Despite the higher initial cost, the system benefits in terms of improved protection, ease of monitoring, and data logging, making it a valuable investment for transformer management.
Authors
- Haripriya Kulkarni (ORCID: https://orcid.org/0000-0002-9748-5723)
- Netra Lokhande (ORCID: https://orcid.org/0000-0002-9457-5475)
- Ashpana Shiralkar (ORCID: https://orcid.org/0000-0002-4216-0120)
- Anagha Soman
- Ashwini Patil (ORCID: https://orcid.org/0000-0003-2132-3899)
- Deepa Shivshant Bhandare (ORCID: https://orcid.org/0000-0002-5782-4786)
- Vidula Jape
- Kamalkishor Maniyar
Publication Details
- Journal
- Journal of Mines Metals and Fuels
- Published
- 2025-07-05
- DOI
- https://doi.org/10.18311/jmmf/2025/49137
- Citations
- 7
- Primary Topic
- Power Systems Fault Detection
- Type
- article
- Field-Weighted Citation Impact
- 8.50