IoT-Based Real-Time Monitoring of Transmission Line Critical Parameters During Fault

Abstract

This paper presents the design and implementation of an IoT-based system for real-time monitoring and fault detection in electrical transmission lines. The proposed solution integrates current transformers (CT), potential transformers (PT), temperature and oil-level sensors with an ATmega328P microcontroller and ESP8266 (NodeMCU) Wi-Fi module. Measured parameters—voltage, current, temperature, and earth leakage—are sampled via the microcontroller’s ADC and multiplexed, then transmitted over TCP/IP to the ThingSpeak cloud platform for dashboard visualization. The system automatically detects over-voltage, under-voltage, short-circuit, open-circuit, and earth-fault conditions, triggering a relay cutoff, LCD display update, and buzzer alert. Laboratory tests confirm accurate fault identification and sub-second response times, demonstrating a low-cost, scalable solution for enhancing grid reliability and reducing maintenance overhead.

Introduction

Electrical transmission lines are vital for power system stability, but traditional fault detection relies on manual inspections and post-fault analysis, causing delays. This study presents a prototype IoT-based monitoring system for near-real-time fault detection and health monitoring of transmission lines.

The system architecture includes four modules:

• Sensing: Uses a potential transformer for voltage, ACS712 sensor for current, temperature sensors, and earth-fault sensors.

• Processing: An ATmega328P microcontroller reads sensor data and detects faults based on predefined thresholds.

• Communication: A NodeMCU ESP8266 Wi-Fi module sends sensor data every second in JSON format to a cloud platform (ThingSpeak).

• Alerting & Control: Includes relays to disconnect loads during faults and local alerts via LCD and buzzer.

The hardware is implemented on a custom PCB powered from 230 VAC with necessary voltage regulation and support circuitry. The prototype enables continuous, remote monitoring and rapid fault isolation, improving transmission line reliability and reducing downtime.

Conclusion

We have demonstrated a cost-effective IoT-enabled monitoring system that achieves real-time fault detection in transmission lines. The integration of embedded sensing, wireless communication, and cloud visualization reduces human intervention and accelerates fault response, enhancing grid reliability. Future work will extend the design to three-phase monitoring, incorporate long-range communication (LoRa/GSM), and apply machine-learning algorithms for predictive maintenance.

References

[1] R. A. D. S. Pawar, “Health condition monitoring system for distribution transformer using Internet of Things (IoT),” in Proc. ICCMC, 2017. [2] “Internet of Things (IoT),” Techopedia. [Online]. Available: www.techopedia.com/definition/28247/internet-of-things-iot. [3] M. M. Ballal and S. S. Mukund, “Online condition monitoring system for substation and service transformer,” IET Electric Power Applications, vol. 11, no. 7, pp. 1187–1195, 2017. [4] X. D. Wang et al., “WRC-SDT: A hybrid online detection method for offshore wind-farm transmission lines,” IEEE Access, vol. 8, pp. 3022639, 2020. [5] A. Abu-Siada, “A novel online technique to detect power transformer winding faults,” IEEE Trans. Power Delivery, vol. 27, no. 2, pp. 849–857, 2012.

Copyright

Copyright © 2025 Vidya Sanjaykumar Bandgar, Jaydeep Vikas Kamble, Sourabh Sanjay Gatare, Ramesh Shankar Dubal, Shoaib Firoj Mujawar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.