Global Temperature Sensing for an Operating Power Transformer Based on Raman Scattering.

Area of Science:

• Electrical Engineering
• Materials Science
• Sensor Technology

Background:

• Traditional power transformer monitoring lacks comprehensive internal thermal data.
• Existing methods are insufficient for detecting critical internal hotspots.
• Accurate thermal monitoring is crucial for transformer longevity and grid reliability.

Purpose of the Study:

• To develop and validate a distributed fiber optic sensor (DFOS) for internal temperature monitoring in a 35 kV power transformer.
• To achieve global sensing capability for real-time thermal mapping within the transformer.
• To improve the accuracy of hotspot detection and provide data for design optimization.

Main Methods:

• Highly integrating a DFOS with electromagnetic wires inside an operating 35 kV power transformer prototype.
• Conducting strict ex-factory tests to qualify the transformer for power grid application.
• Applying Gaussian convolution for signal processing to accurately trace internal temperature distributions and identify hotspots.

Main Results:

• The developed DFOS system achieved stable operation with ±0.2 °C temperature accuracy and 0.8 m spatial positioning accuracy.
• Accurate hotspot locations were identified on both high voltage (89.1% height, 55 °C) and low voltage (89.7% height, 77.5 °C) windings.
• The precise hotspot data challenged traditional assumptions about winding temperature distribution.

Conclusions:

• The integrated DFOS offers a novel, non-destructive method for internal condition monitoring of power transformers.
• This technology provides essential reference data for transformer manufacturers, enabling design improvements.
• DFOS presents a promising future for enhanced monitoring in the high-voltage electrical apparatus industry.