Summary

This paper presents an indirect method for locating faults in high-voltage cable lines by utilizing distributed temperature monitoring. Ensuring the reliability of these lines is critical for urban power systems, particularly for those supplying strategic and critical infrastructure.

Overheating compromises reliability and can trigger emergency faults leading to outages with serious consequences. The proposed method is based on using an optical fiber integrated into the cable structure as a Distributed Temperature Sensing (DTS) element.

The system analyses the backscatter of laser radiation. Temperature variations alter the characteristics of light propagation in the fiber. The method employs Raman scattering, where the anti-Stokes component is temperature-dependent, in contrast to the stable Stokes component. By calculating the intensity ratio of these components, the system determines temperature with high accuracy.

Two years of system implementation and analysis have enabled the construction of complete temperature profiles for high-voltage cable lines up to 40 km (and modern DTS systems allow ranges exceeding 100 km) in length, with a spatial resolution of 1 m and a temperature accuracy of 0.1 °C. This capability allows recording temperature exceedances relative to load and the identification of local overheating at crossings with heating pipelines and other urban utility networks. Consequently, the method detects temperature anomalies at potential fault locations, prevents emergency shutdowns, and enables precise fault localization.

Additional informations

Publication type Session Materials
Reference B1_12634_2026
Publication year
Publisher CIGRE
Country Serbia
Study committees
File size 1 MB
Price for non member 30 €
Price for member 30 €

Authors

IVANOV Mikhail - PJSC «Rosseti Lenenergo» Cable Line Service 35-220 kV Russia

Keywords

Cable, Monitoring, Temperature, Diagnostics, Fiber Optic, Sensor, Raman Scattering, Hotspot, Damage, Fault, Reliability

Indirect Fault Location in Cable Lines Using Distributed Temperature Sensing